Author: "P. Prost" - Searchworks@Jio Institute Digital Library Search Results

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1,689 results on '"P. Prost"'

1. Multiple Instance Learning with Coarse-to-Fine Self-Distillation

Author: Wu, Shuyang, Qiu, Yifu, Nearchou, Ines P., Prost, Sandrine, Fallowfield, Jonathan A., Bilen, Hakan, and Kendall, Timothy J.
Subjects: Computer Science - Computer Vision and Pattern Recognition
Abstract: Multiple Instance Learning (MIL) for whole slide image (WSI) analysis in computational pathology often neglects instance-level learning as supervision is typically provided only at the bag level. In this work, we present PathMIL, a framework designed to improve MIL through two perspectives: (1) employing instance-level supervision and (2) learning inter-instance contextual information on bag level. Firstly, we propose a novel Coarse-to-Fine Self-Distillation (CFSD) paradigm, to probe and distil a classifier trained with bag-level information to obtain instance-level labels which could effectively provide the supervision for the same classifier in a finer way. Secondly, to capture inter-instance contextual information in WSI, we propose Two-Dimensional Positional Encoding (2DPE), which encodes the spatial appearance of instances within a bag. We also theoretically and empirically prove the instance-level learnability of CFSD. PathMIL is evaluated on multiple benchmarking tasks, including subtype classification (TCGA-NSCLC), tumour classification (CAMELYON16), and an internal benchmark for breast cancer receptor status classification. Our method achieves state-of-the-art performance, with AUC scores of 0.9152 and 0.8524 for estrogen and progesterone receptor status classification, respectively, an AUC of 0.9618 for subtype classification, and 0.8634 for tumour classification, surpassing existing methods.
Published: 2025

2. InfAlign: Inference-aware language model alignment

Author: Balashankar, Ananth, Sun, Ziteng, Berant, Jonathan, Eisenstein, Jacob, Collins, Michael, Hutter, Adrian, Lee, Jong, Nagpal, Chirag, Prost, Flavien, Sinha, Aradhana, Suresh, Ananda Theertha, and Beirami, Ahmad
Subjects: Computer Science - Machine Learning, Computer Science - Computation and Language, Computer Science - Information Theory
Abstract: Language model alignment is a critical step in training modern generative language models. Alignment targets to improve win rate of a sample from the aligned model against the base model. Today, we are increasingly using inference-time algorithms (e.g., Best-of-N, controlled decoding, tree search) to decode from language models rather than standard sampling. We show that this train/test mismatch makes standard RLHF framework sub-optimal in view of such inference-time methods. To this end, we propose a framework for inference-aware alignment (InfAlign), which aims to optimize inference-time win rate of the aligned policy against the base model. We prove that for any inference-time decoding procedure, the optimal aligned policy is the solution to the standard RLHF problem with a transformation of the reward. This motivates us to provide the calibrate-and-transform RL (InfAlign-CTRL) algorithm to solve this problem, which involves a reward calibration step and a KL-regularized reward maximization step with a transformation of the calibrated reward. For best-of-N sampling and best-of-N jailbreaking, we propose specific transformations offering up to 3-8% improvement on inference-time win rates. Finally, we also show that our proposed reward calibration method is a strong baseline for optimizing standard win rate.
Published: 2024

3. Simplified magnet design and manufacture based on patterning of wide conductors

Author: Botelho, Diego Pereira, Prost, Victor, Pereira, Luana Barbosa Pina, and Volpe, Francesco A.
Subjects: Physics - Plasma Physics
Abstract: The fabrication and assembly of High Temperature Superconducting (HTS) magnets can be significantly streamlined by (1) direct deposition of HTS onto modular components and (2) laser-ablated grooves to bound and guide the electric currents over the superconducting surfaces. "Coils" bounded by consecutive grooves can be individually powered, or connected in series, or in parallel. Applications include plasma-confinement devices such as stellarators and magnets for particle accelerators. On the way to HTS magnets generating more complicated three-dimensional fields, this paper validates the technique for two cylindrically symmetric magnets made of standard conductors. The optimized grooving pattern is considered as an inverse problem that is resolved using a least squares approach with Tikhonov regularization. This approach was first applied to design a magnet that replicates the magnetic field configuration of a microwave source of the gyrotron type. Gyrotrons require a particular profile of magnetic field, which our aluminium prototype successfully reproduced with 10$^{-1}$ precision. The second one, in copper, is a small-size, reduced-field magnet for Magnetic Resonance Imaging (MRI). This application requires highly uniform longitudinal fields. The achieved precision (about 50 ppm) is exceptional for an MRI magnet just getting out of the factory, and can easily meet hospital standards after minimal shimming or other error field correction. Future work and other potential applications of wide, patterned conductors or superconductors are also discussed., Comment: 11 pages, 14 figures
Published: 2024

4. Inducing Group Fairness in Prompt-Based Language Model Decisions

Author: Atwood, James, Scherrer, Nino, Lahoti, Preethi, Balashankar, Ananth, Prost, Flavien, and Beirami, Ahmad
Subjects: Computer Science - Machine Learning, Computer Science - Artificial Intelligence, Computer Science - Computers and Society
Abstract: Classifiers are used throughout industry to enforce policies, ranging from the detection of toxic content to age-appropriate content filtering. While these classifiers serve important functions, it is also essential that they are built in ways that minimize unfair biases for users. One such fairness consideration is called group fairness, which desires that different sub-population of users receive equal treatment. This is a well-studied problem in the context of 'classical' classifiers. However, the emergence of prompt-based language model (LM) decision making has created new opportunities to solve text-based classification tasks, and the fairness properties of these new classifiers are not yet well understood. Further, the `remediation toolkit' is incomplete for LM-based decision makers and little is understood about how to improve decision maker group fairness while maintaining classifier performance. This work sets out to add more tools to that toolbox. We introduce adaptations of existing effective approaches from the classical classifier fairness to the prompt-based classifier space. We also devise simple methods that take advantage of the new structure of prompt-based decision makers and operate at the prompt level. We compare these approaches empirically on real data. Our results suggest that adaptations of approaches that are effective for classical classifiers remain effective in the LM-based classifier environment. However, there is room for further exploration of prompt-based remediation methods (and other remediation methods that take advantage of LM structure).
Published: 2024

5. The effect of degenerative scolioisis on segmental thoracolumbar sagittal alignment compared to age- and pelvic incidence-matched reference values

Author: Lamas, Vincent, Chapon, Renan, Prost, Solène, Blondel, Benjamin, Fuentes, Stéphane, Sauleau, Erik André, and Charles, Yann Philippe
Published: 2025
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6. Doctor, when can I drive? Charakterisierung des Fahrverhaltens orthopädischer und unfallchirurgischer Patienten anhand einer prospektiven Fragebogenstudie

Author: Lakomek, Felix, Hilsmann, Falk, Schiffner, Erik, Gehrmann, Sebastian, Schöps, Dominique, Prost, Max, Windolf, Joachim, and Latz, David
Published: 2025
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7. On the consistency of supervised learning with missing values

Author: Josse, Julie, Chen, Jacob M., Prost, Nicolas, Varoquaux, Gaël, and Scornet, Erwan
Published: 2024
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8. Emergence of bidirectional cell laning from collective contact guidance

Author: Lacroix, Mathilde, Smeets, Bart, Blanch-Mercader, Carlès, Bell, Samuel, Giuglaris, Caroline, Chen, Hsiang-Ying, Prost, Jacques, and Silberzan, Pascal
Subjects: Physics - Biological Physics
Abstract: Directed collective cell migration is central in morphogenesis, wound healing and cancer progression1,2. Although it is well-accepted that the molecular anisotropy of the micro-environment guides this migration3,4, its impact on the pattern of the cell flows remains largely unexplored. Studying confluent human bronchial epithelial cells (HBECs) in vitro, we show that subcellular microgrooves elicit a polar mode of collective migration in millimeter-long bidirectional lanes that are much wider than a cell size, even though cell flows are highly disordered on featureless surfaces 5. This directed flocking-like transition6,7 can be accounted for by a hydrodynamic theory of active polar fluids and corresponding numerical simulations. This model further predicts that anisotropic friction resulting from the grooves lowers the threshold of the transition, which we confirm experimentally. Therefore, microscopic anisotropy of the environment not only directs the collective motion of the cells in the easy direction, but also shapes the cell migration pattern. Flow patterns induced by collective contact guidance are thus markedly different from those induced by supracellular confinement8, demonstrating that all length-scales of the micro-environment must be considered in a comprehensive description of collective migration. Furthermore, artificial microtopographies designed from theoretical considerations can provide a rational strategy to direct cells to specific geometries and functions, which has broad implications, for instance, for tissue engineering strategies in organoid morphogenesis., Comment: Nature Physics, 2024
Published: 2024
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9. Spontaneous flows in active smectics with dislocations

Author: Lin, Shao-Zhen, Jülicher, Frank, Prost, Jacques, and Rupprecht, Jean-Francois
Subjects: Condensed Matter - Soft Condensed Matter, Physics - Biological Physics
Abstract: We construct a hydrodynamic theory of active smectics A in two-dimensional space, including the creation/annihilation and motility of dislocations with Burgers' number $\pm1$. We derive analytical criteria on the set of parameters that lead to flows. We show that the motility of dislocations can lead to flow transitions with distinct features from the previously reported active Helfrich--Hurault shear instability with, notably, a first-order transition in the velocity from quiescence to turbulence., Comment: 5 pages, 5 figures
Published: 2024

10. Stochastic nanoswimmer: a multistate model for enzyme self-propulsion and enhanced diffusion

Author: Vishen, Amit Singh, Prost, Jacques, and Rao, Madan
Subjects: Condensed Matter - Soft Condensed Matter, Condensed Matter - Statistical Mechanics, Physics - Biological Physics
Abstract: Several enzymes exhibit enhanced diffusion in the presence of a substrate. One explanation of this enhancement arises from fluctuating dimer models, which suggest that enzymes have a higher diffusion constant when interacting with substrates compared to when they are free. Another possible mechanism, suggested in both experimental and theoretical studies, is that enzymes act as nanoswimmers. However, existing nanoswimmer models have struggled to account for the exceptionally high self-propulsion speeds observed in experiments, with estimated increases in diffusion due to self-propulsion found to be minimal. In this study, we model enzymes as dimers with fluctuating mobility. We show that even dimers can exhibit run-and-tumble motion when transitioning between states of varying mobility within the enzymatic cycle. By exploring a three-state enzymatic cycle, we identify the conditions under which self-propulsion speeds and increases in diffusion rate consistent with experimental observations can be achieved.
Published: 2024

11. Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context

Author: Gemini Team, Georgiev, Petko, Lei, Ving Ian, Burnell, Ryan, Bai, Libin, Gulati, Anmol, Tanzer, Garrett, Vincent, Damien, Pan, Zhufeng, Wang, Shibo, Mariooryad, Soroosh, Ding, Yifan, Geng, Xinyang, Alcober, Fred, Frostig, Roy, Omernick, Mark, Walker, Lexi, Paduraru, Cosmin, Sorokin, Christina, Tacchetti, Andrea, Gaffney, Colin, Daruki, Samira, Sercinoglu, Olcan, Gleicher, Zach, Love, Juliette, Voigtlaender, Paul, Jain, Rohan, Surita, Gabriela, Mohamed, Kareem, Blevins, Rory, Ahn, Junwhan, Zhu, Tao, Kawintiranon, Kornraphop, Firat, Orhan, Gu, Yiming, Zhang, Yujing, Rahtz, Matthew, Faruqui, Manaal, Clay, Natalie, Gilmer, Justin, Co-Reyes, JD, Penchev, Ivo, Zhu, Rui, Morioka, Nobuyuki, Hui, Kevin, Haridasan, Krishna, Campos, Victor, Mahdieh, Mahdis, Guo, Mandy, Hassan, Samer, Kilgour, Kevin, Vezer, Arpi, Cheng, Heng-Tze, de Liedekerke, Raoul, Goyal, Siddharth, Barham, Paul, Strouse, DJ, Noury, Seb, Adler, Jonas, Sundararajan, Mukund, Vikram, Sharad, Lepikhin, Dmitry, Paganini, Michela, Garcia, Xavier, Yang, Fan, Valter, Dasha, Trebacz, Maja, Vodrahalli, Kiran, Asawaroengchai, Chulayuth, Ring, Roman, Kalb, Norbert, Soares, Livio Baldini, Brahma, Siddhartha, Steiner, David, Yu, Tianhe, Mentzer, Fabian, He, Antoine, Gonzalez, Lucas, Xu, Bibo, Kaufman, Raphael Lopez, Shafey, Laurent El, Oh, Junhyuk, Hennigan, Tom, Driessche, George van den, Odoom, Seth, Lucic, Mario, Roelofs, Becca, Lall, Sid, Marathe, Amit, Chan, Betty, Ontanon, Santiago, He, Luheng, Teplyashin, Denis, Lai, Jonathan, Crone, Phil, Damoc, Bogdan, Ho, Lewis, Riedel, Sebastian, Lenc, Karel, Yeh, Chih-Kuan, Chowdhery, Aakanksha, Xu, Yang, Kazemi, Mehran, Amid, Ehsan, Petrushkina, Anastasia, Swersky, Kevin, Khodaei, Ali, Chen, Gowoon, Larkin, Chris, Pinto, Mario, Yan, Geng, Badia, Adria Puigdomenech, Patil, Piyush, Hansen, Steven, Orr, Dave, Arnold, Sebastien M. R., Grimstad, Jordan, Dai, Andrew, Douglas, Sholto, Sinha, Rishika, Yadav, Vikas, Chen, Xi, Gribovskaya, Elena, Austin, Jacob, Zhao, Jeffrey, Patel, Kaushal, Komarek, Paul, Austin, Sophia, Borgeaud, Sebastian, Friso, Linda, Goyal, Abhimanyu, Caine, Ben, Cao, Kris, Chung, Da-Woon, Lamm, Matthew, Barth-Maron, Gabe, Kagohara, Thais, Olszewska, Kate, Chen, Mia, Shivakumar, Kaushik, Agarwal, Rishabh, Godhia, Harshal, Rajwar, Ravi, Snaider, Javier, Dotiwalla, Xerxes, Liu, Yuan, Barua, Aditya, Ungureanu, Victor, Zhang, Yuan, Batsaikhan, Bat-Orgil, Wirth, Mateo, Qin, James, Danihelka, Ivo, Doshi, Tulsee, Chadwick, Martin, Chen, Jilin, Jain, Sanil, Le, Quoc, Kar, Arjun, Gurumurthy, Madhu, Li, Cheng, Sang, Ruoxin, Liu, Fangyu, Lamprou, Lampros, Munoz, Rich, Lintz, Nathan, Mehta, Harsh, Howard, Heidi, Reynolds, Malcolm, Aroyo, Lora, Wang, Quan, Blanco, Lorenzo, Cassirer, Albin, Griffith, Jordan, Das, Dipanjan, Lee, Stephan, Sygnowski, Jakub, Fisher, Zach, Besley, James, Powell, Richard, Ahmed, Zafarali, Paulus, Dominik, Reitter, David, Borsos, Zalan, Joshi, Rishabh, Pope, Aedan, Hand, Steven, Selo, Vittorio, Jain, Vihan, Sethi, Nikhil, Goel, Megha, Makino, Takaki, May, Rhys, Yang, Zhen, Schalkwyk, Johan, Butterfield, Christina, Hauth, Anja, Goldin, Alex, Hawkins, Will, Senter, Evan, Brin, Sergey, Woodman, Oliver, Ritter, Marvin, Noland, Eric, Giang, Minh, Bolina, Vijay, Lee, Lisa, Blyth, Tim, Mackinnon, Ian, Reid, Machel, Sarvana, Obaid, Silver, David, Chen, Alexander, Wang, Lily, Maggiore, Loren, Chang, Oscar, Attaluri, Nithya, Thornton, Gregory, Chiu, Chung-Cheng, Bunyan, Oskar, Levine, Nir, Chung, Timothy, Eltyshev, Evgenii, Si, Xiance, Lillicrap, Timothy, Brady, Demetra, Aggarwal, Vaibhav, Wu, Boxi, Xu, Yuanzhong, McIlroy, Ross, Badola, Kartikeya, Sandhu, Paramjit, Moreira, Erica, Stokowiec, Wojciech, Hemsley, Ross, Li, Dong, Tudor, Alex, Shyam, Pranav, Rahimtoroghi, Elahe, Haykal, Salem, Sprechmann, Pablo, Zhou, Xiang, Mincu, Diana, Li, Yujia, Addanki, Ravi, Krishna, Kalpesh, Wu, Xiao, Frechette, Alexandre, Eyal, Matan, Dafoe, Allan, Lacey, Dave, Whang, Jay, Avrahami, Thi, Zhang, Ye, Taropa, Emanuel, Lin, Hanzhao, Toyama, Daniel, Rutherford, Eliza, Sano, Motoki, Choe, HyunJeong, Tomala, Alex, Safranek-Shrader, Chalence, Kassner, Nora, Pajarskas, Mantas, Harvey, Matt, Sechrist, Sean, Fortunato, Meire, Lyu, Christina, Elsayed, Gamaleldin, Kuang, Chenkai, Lottes, James, Chu, Eric, Jia, Chao, Chen, Chih-Wei, Humphreys, Peter, Baumli, Kate, Tao, Connie, Samuel, Rajkumar, Santos, Cicero Nogueira dos, Andreassen, Anders, Rakićević, Nemanja, Grewe, Dominik, Kumar, Aviral, Winkler, Stephanie, Caton, Jonathan, Brock, Andrew, Dalmia, Sid, Sheahan, Hannah, Barr, Iain, Miao, Yingjie, Natsev, Paul, Devlin, Jacob, Behbahani, Feryal, Prost, Flavien, Sun, Yanhua, Myaskovsky, Artiom, Pillai, Thanumalayan Sankaranarayana, Hurt, Dan, Lazaridou, Angeliki, Xiong, Xi, Zheng, Ce, Pardo, Fabio, Li, Xiaowei, Horgan, Dan, Stanton, Joe, Ambar, Moran, Xia, Fei, Lince, Alejandro, Wang, Mingqiu, Mustafa, Basil, Webson, Albert, Lee, Hyo, Anil, Rohan, Wicke, Martin, Dozat, Timothy, Sinha, Abhishek, Piqueras, Enrique, Dabir, Elahe, Upadhyay, Shyam, Boral, Anudhyan, Hendricks, Lisa Anne, Fry, Corey, Djolonga, Josip, Su, Yi, Walker, Jake, Labanowski, Jane, Huang, Ronny, Misra, Vedant, Chen, Jeremy, Skerry-Ryan, RJ, Singh, Avi, Rijhwani, Shruti, Yu, Dian, Castro-Ros, Alex, Changpinyo, Beer, Datta, Romina, Bagri, Sumit, Hrafnkelsson, Arnar Mar, Maggioni, Marcello, Zheng, Daniel, Sulsky, Yury, Hou, Shaobo, Paine, Tom Le, Yang, Antoine, Riesa, Jason, Rogozinska, Dominika, Marcus, Dror, Badawy, Dalia El, Zhang, Qiao, Wang, Luyu, Miller, Helen, Greer, Jeremy, Sjos, Lars Lowe, Nova, Azade, Zen, Heiga, Chaabouni, Rahma, Rosca, Mihaela, Jiang, Jiepu, Chen, Charlie, Liu, Ruibo, Sainath, Tara, Krikun, Maxim, Polozov, Alex, Lespiau, Jean-Baptiste, Newlan, Josh, Cankara, Zeyncep, Kwak, Soo, Xu, Yunhan, Chen, Phil, Coenen, Andy, Meyer, Clemens, Tsihlas, Katerina, Ma, Ada, Gottweis, Juraj, Xing, Jinwei, Gu, Chenjie, Miao, Jin, Frank, Christian, Cankara, Zeynep, Ganapathy, Sanjay, Dasgupta, Ishita, Hughes-Fitt, Steph, Chen, Heng, Reid, David, Rong, Keran, Fan, Hongmin, van Amersfoort, Joost, Zhuang, Vincent, Cohen, Aaron, Gu, Shixiang Shane, Mohananey, Anhad, Ilic, Anastasija, Tobin, Taylor, Wieting, John, Bortsova, Anna, Thacker, Phoebe, Wang, Emma, Caveness, Emily, Chiu, Justin, Sezener, Eren, Kaskasoli, Alex, Baker, Steven, Millican, Katie, Elhawaty, Mohamed, Aisopos, Kostas, Lebsack, Carl, Byrd, Nathan, Dai, Hanjun, Jia, Wenhao, Wiethoff, Matthew, Davoodi, Elnaz, Weston, Albert, Yagati, Lakshman, Ahuja, Arun, Gao, Isabel, Pundak, Golan, Zhang, Susan, Azzam, Michael, Sim, Khe Chai, Caelles, Sergi, Keeling, James, Sharma, Abhanshu, Swing, Andy, Li, YaGuang, Liu, Chenxi, Bostock, Carrie Grimes, Bansal, Yamini, Nado, Zachary, Anand, Ankesh, Lipschultz, Josh, Karmarkar, Abhijit, Proleev, Lev, Ittycheriah, Abe, Yeganeh, Soheil Hassas, Polovets, George, Faust, Aleksandra, Sun, Jiao, Rrustemi, Alban, Li, Pen, Shivanna, Rakesh, Liu, Jeremiah, Welty, Chris, Lebron, Federico, Baddepudi, Anirudh, Krause, Sebastian, Parisotto, Emilio, Soricut, Radu, Xu, Zheng, Bloxwich, Dawn, Johnson, Melvin, Neyshabur, Behnam, Mao-Jones, Justin, Wang, Renshen, Ramasesh, Vinay, Abbas, Zaheer, Guez, Arthur, Segal, Constant, Nguyen, Duc Dung, Svensson, James, Hou, Le, York, Sarah, Milan, Kieran, Bridgers, Sophie, Gworek, Wiktor, Tagliasacchi, Marco, Lee-Thorp, James, Chang, Michael, Guseynov, Alexey, Hartman, Ale Jakse, Kwong, Michael, Zhao, Ruizhe, Kashem, Sheleem, Cole, Elizabeth, Miech, Antoine, Tanburn, Richard, Phuong, Mary, Pavetic, Filip, Cevey, Sebastien, Comanescu, Ramona, Ives, Richard, Yang, Sherry, Du, Cosmo, Li, Bo, Zhang, Zizhao, Iinuma, Mariko, Hu, Clara Huiyi, Roy, Aurko, Bijwadia, Shaan, Zhu, Zhenkai, Martins, Danilo, Saputro, Rachel, Gergely, Anita, Zheng, Steven, Jia, Dawei, Antonoglou, Ioannis, Sadovsky, Adam, Gu, Shane, Bi, Yingying, Andreev, Alek, Samangooei, Sina, Khan, Mina, Kocisky, Tomas, Filos, Angelos, Kumar, Chintu, Bishop, Colton, Yu, Adams, Hodkinson, Sarah, Mittal, Sid, Shah, Premal, Moufarek, Alexandre, Cheng, Yong, Bloniarz, Adam, Lee, Jaehoon, Pejman, Pedram, Michel, Paul, Spencer, Stephen, Feinberg, Vladimir, Xiong, Xuehan, Savinov, Nikolay, Smith, Charlotte, Shakeri, Siamak, Tran, Dustin, Chesus, Mary, Bohnet, Bernd, Tucker, George, von Glehn, Tamara, Muir, Carrie, Mao, Yiran, Kazawa, Hideto, Slone, Ambrose, Soparkar, Kedar, Shrivastava, Disha, Cobon-Kerr, James, Sharman, Michael, Pavagadhi, Jay, Araya, Carlos, Misiunas, Karolis, Ghelani, Nimesh, Laskin, Michael, Barker, David, Li, Qiujia, Briukhov, Anton, Houlsby, Neil, Glaese, Mia, Lakshminarayanan, Balaji, Schucher, Nathan, Tang, Yunhao, Collins, Eli, Lim, Hyeontaek, Feng, Fangxiaoyu, Recasens, Adria, Lai, Guangda, Magni, Alberto, De Cao, Nicola, Siddhant, Aditya, Ashwood, Zoe, Orbay, Jordi, Dehghani, Mostafa, Brennan, Jenny, He, Yifan, Xu, Kelvin, Gao, Yang, Saroufim, Carl, Molloy, James, Wu, Xinyi, Arnold, Seb, Chang, Solomon, Schrittwieser, Julian, Buchatskaya, Elena, Radpour, Soroush, Polacek, Martin, Giordano, Skye, Bapna, Ankur, Tokumine, Simon, Hellendoorn, Vincent, Sottiaux, Thibault, Cogan, Sarah, Severyn, Aliaksei, Saleh, Mohammad, Thakoor, Shantanu, Shefey, Laurent, Qiao, Siyuan, Gaba, Meenu, Chang, Shuo-yiin, Swanson, Craig, Zhang, Biao, Lee, Benjamin, Rubenstein, Paul Kishan, Song, Gan, Kwiatkowski, Tom, Koop, Anna, Kannan, Ajay, Kao, David, Schuh, Parker, Stjerngren, Axel, Ghiasi, Golnaz, Gibson, Gena, Vilnis, Luke, Yuan, Ye, Ferreira, Felipe Tiengo, Kamath, Aishwarya, Klimenko, Ted, Franko, Ken, Xiao, Kefan, Bhattacharya, Indro, Patel, Miteyan, Wang, Rui, Morris, Alex, Strudel, Robin, Sharma, Vivek, Choy, Peter, Hashemi, Sayed Hadi, Landon, Jessica, Finkelstein, Mara, Jhakra, Priya, Frye, Justin, Barnes, Megan, Mauger, Matthew, Daun, Dennis, Baatarsukh, Khuslen, Tung, Matthew, Farhan, Wael, Michalewski, Henryk, Viola, Fabio, Quitry, Felix de Chaumont, Lan, Charline Le, Hudson, Tom, Wang, Qingze, Fischer, Felix, Zheng, Ivy, White, Elspeth, Dragan, Anca, Alayrac, Jean-baptiste, Ni, Eric, Pritzel, Alexander, Iwanicki, Adam, Isard, Michael, Bulanova, Anna, Zilka, Lukas, Dyer, Ethan, Sachan, Devendra, Srinivasan, Srivatsan, Muckenhirn, Hannah, Cai, Honglong, Mandhane, Amol, Tariq, Mukarram, Rae, Jack W., Wang, Gary, Ayoub, Kareem, FitzGerald, Nicholas, Zhao, Yao, Han, Woohyun, Alberti, Chris, Garrette, Dan, Krishnakumar, Kashyap, Gimenez, Mai, Levskaya, Anselm, Sohn, Daniel, Matak, Josip, Iturrate, Inaki, Chang, Michael B., Xiang, Jackie, Cao, Yuan, Ranka, Nishant, Brown, Geoff, Hutter, Adrian, Mirrokni, Vahab, Chen, Nanxin, Yao, Kaisheng, Egyed, Zoltan, Galilee, Francois, Liechty, Tyler, Kallakuri, Praveen, Palmer, Evan, Ghemawat, Sanjay, Liu, Jasmine, Tao, David, Thornton, Chloe, Green, Tim, Jasarevic, Mimi, Lin, Sharon, Cotruta, Victor, Tan, Yi-Xuan, Fiedel, Noah, Yu, Hongkun, Chi, Ed, Neitz, Alexander, Heitkaemper, Jens, Sinha, Anu, Zhou, Denny, Sun, Yi, Kaed, Charbel, Hulse, Brice, Mishra, Swaroop, Georgaki, Maria, Kudugunta, Sneha, Farabet, Clement, Shafran, Izhak, Vlasic, Daniel, Tsitsulin, Anton, Ananthanarayanan, Rajagopal, Carin, Alen, Su, Guolong, Sun, Pei, V, Shashank, Carvajal, Gabriel, Broder, Josef, Comsa, Iulia, Repina, Alena, Wong, William, Chen, Warren Weilun, Hawkins, Peter, Filonov, Egor, Loher, Lucia, Hirnschall, Christoph, Wang, Weiyi, Ye, Jingchen, Burns, Andrea, Cate, Hardie, Wright, Diana Gage, Piccinini, Federico, Zhang, Lei, Lin, Chu-Cheng, Gog, Ionel, Kulizhskaya, Yana, Sreevatsa, Ashwin, Song, Shuang, Cobo, Luis C., Iyer, Anand, Tekur, Chetan, Garrido, Guillermo, Xiao, Zhuyun, Kemp, Rupert, Zheng, Huaixiu Steven, Li, Hui, Agarwal, Ananth, Ngani, Christel, Goshvadi, Kati, Santamaria-Fernandez, Rebeca, Fica, Wojciech, Chen, Xinyun, Gorgolewski, Chris, Sun, Sean, Garg, Roopal, Ye, Xinyu, Eslami, S. M. Ali, Hua, Nan, Simon, Jon, Joshi, Pratik, Kim, Yelin, Tenney, Ian, Potluri, Sahitya, Thiet, Lam Nguyen, Yuan, Quan, Luisier, Florian, Chronopoulou, Alexandra, Scellato, Salvatore, Srinivasan, Praveen, Chen, Minmin, Koverkathu, Vinod, Dalibard, Valentin, Xu, Yaming, Saeta, Brennan, Anderson, Keith, Sellam, Thibault, Fernando, Nick, Huot, Fantine, Jung, Junehyuk, Varadarajan, Mani, Quinn, Michael, Raul, Amit, Le, Maigo, Habalov, Ruslan, Clark, Jon, Jalan, Komal, Bullard, Kalesha, Singhal, Achintya, Luong, Thang, Wang, Boyu, Rajayogam, Sujeevan, Eisenschlos, Julian, Jia, Johnson, Finchelstein, Daniel, Yakubovich, Alex, Balle, Daniel, Fink, Michael, Agarwal, Sameer, Li, Jing, Dvijotham, Dj, Pal, Shalini, Kang, Kai, Konzelmann, Jaclyn, Beattie, Jennifer, Dousse, Olivier, Wu, Diane, Crocker, Remi, Elkind, Chen, Jonnalagadda, Siddhartha Reddy, Lee, Jong, Holtmann-Rice, Dan, Kallarackal, Krystal, Liu, Rosanne, Vnukov, Denis, Vats, Neera, Invernizzi, Luca, Jafari, Mohsen, Zhou, Huanjie, Taylor, Lilly, Prendki, Jennifer, Wu, Marcus, Eccles, Tom, Liu, Tianqi, Kopparapu, Kavya, Beaufays, Francoise, Angermueller, Christof, Marzoca, Andreea, Sarcar, Shourya, Dib, Hilal, Stanway, Jeff, Perbet, Frank, Trdin, Nejc, Sterneck, Rachel, Khorlin, Andrey, Li, Dinghua, Wu, Xihui, Goenka, Sonam, Madras, David, Goldshtein, Sasha, Gierke, Willi, Zhou, Tong, Liu, Yaxin, Liang, Yannie, White, Anais, Li, Yunjie, Singh, Shreya, Bahargam, Sanaz, Epstein, Mark, Basu, Sujoy, Lao, Li, Ozturel, Adnan, Crous, Carl, Zhai, Alex, Lu, Han, Tung, Zora, Gaur, Neeraj, Walton, Alanna, Dixon, Lucas, Zhang, Ming, Globerson, Amir, Uy, Grant, Bolt, Andrew, Wiles, Olivia, Nasr, Milad, Shumailov, Ilia, Selvi, Marco, Piccinno, Francesco, Aguilar, Ricardo, McCarthy, Sara, Khalman, Misha, Shukla, Mrinal, Galic, Vlado, Carpenter, John, Villela, Kevin, Zhang, Haibin, Richardson, Harry, Martens, James, Bosnjak, Matko, Belle, Shreyas Rammohan, Seibert, Jeff, Alnahlawi, Mahmoud, McWilliams, Brian, Singh, Sankalp, Louis, Annie, Ding, Wen, Popovici, Dan, Simicich, Lenin, Knight, Laura, Mehta, Pulkit, Gupta, Nishesh, Shi, Chongyang, Fatehi, Saaber, Mitrovic, Jovana, Grills, Alex, Pagadora, Joseph, Munkhdalai, Tsendsuren, Petrova, Dessie, Eisenbud, Danielle, Zhang, Zhishuai, Yates, Damion, Mittal, Bhavishya, Tripuraneni, Nilesh, Assael, Yannis, Brovelli, Thomas, Jain, Prateek, Velimirovic, Mihajlo, Akbulut, Canfer, Mu, Jiaqi, Macherey, Wolfgang, Kumar, Ravin, Xu, Jun, Qureshi, Haroon, Comanici, Gheorghe, Wiesner, Jeremy, Gong, Zhitao, Ruddock, Anton, Bauer, Matthias, Felt, Nick, GP, Anirudh, Arnab, Anurag, Zelle, Dustin, Rothfuss, Jonas, Rosgen, Bill, Shenoy, Ashish, Seybold, Bryan, Li, Xinjian, Mudigonda, Jayaram, Erdogan, Goker, Xia, Jiawei, Simsa, Jiri, Michi, Andrea, Yao, Yi, Yew, Christopher, Kan, Steven, Caswell, Isaac, Radebaugh, Carey, Elisseeff, Andre, Valenzuela, Pedro, McKinney, Kay, Paterson, Kim, Cui, Albert, Latorre-Chimoto, Eri, Kim, Solomon, Zeng, William, Durden, Ken, Ponnapalli, Priya, Sosea, Tiberiu, Choquette-Choo, Christopher A., Manyika, James, Robenek, Brona, Vashisht, Harsha, Pereira, Sebastien, Lam, Hoi, Velic, Marko, Owusu-Afriyie, Denese, Lee, Katherine, Bolukbasi, Tolga, Parrish, Alicia, Lu, Shawn, Park, Jane, Venkatraman, Balaji, Talbert, Alice, Rosique, Lambert, Cheng, Yuchung, Sozanschi, Andrei, Paszke, Adam, Kumar, Praveen, Austin, Jessica, Li, Lu, Salama, Khalid, Perz, Bartek, Kim, Wooyeol, Dukkipati, Nandita, Baryshnikov, Anthony, Kaplanis, Christos, Sheng, XiangHai, Chervonyi, Yuri, Unlu, Caglar, Casas, Diego de Las, Askham, Harry, Tunyasuvunakool, Kathryn, Gimeno, Felix, Poder, Siim, Kwak, Chester, Miecnikowski, Matt, Dimitriev, Alek, Parisi, Aaron, Liu, Dangyi, Tsai, Tomy, Shevlane, Toby, Kouridi, Christina, Garmon, Drew, Goedeckemeyer, Adrian, Brown, Adam R., Vijayakumar, Anitha, Elqursh, Ali, Jazayeri, Sadegh, Huang, Jin, Carthy, Sara Mc, Hoover, Jay, Kim, Lucy, Kumar, Sandeep, Chen, Wei, Biles, Courtney, Bingham, Garrett, Rosen, Evan, Wang, Lisa, Tan, Qijun, Engel, David, Pongetti, Francesco, de Cesare, Dario, Hwang, Dongseong, Yu, Lily, Pullman, Jennifer, Narayanan, Srini, Levin, Kyle, Gopal, Siddharth, Li, Megan, Aharoni, Asaf, Trinh, Trieu, Lo, Jessica, Casagrande, Norman, Vij, Roopali, Matthey, Loic, Ramadhana, Bramandia, Matthews, Austin, Carey, CJ, Johnson, Matthew, Goranova, Kremena, Shah, Rohin, Ashraf, Shereen, Dasgupta, Kingshuk, Larsen, Rasmus, Wang, Yicheng, Vuyyuru, Manish Reddy, Jiang, Chong, Ijazi, Joana, Osawa, Kazuki, Smith, Celine, Boppana, Ramya Sree, Bilal, Taylan, Koizumi, Yuma, Xu, Ying, Altun, Yasemin, Shabat, Nir, Bariach, Ben, Korchemniy, Alex, Choo, Kiam, Ronneberger, Olaf, Iwuanyanwu, Chimezie, Zhao, Shubin, Soergel, David, Hsieh, Cho-Jui, Cai, Irene, Iqbal, Shariq, Sundermeyer, Martin, Chen, Zhe, Bursztein, Elie, Malaviya, Chaitanya, Biadsy, Fadi, Shroff, Prakash, Dhillon, Inderjit, Latkar, Tejasi, Dyer, Chris, Forbes, Hannah, Nicosia, Massimo, Nikolaev, Vitaly, Greene, Somer, Georgiev, Marin, Wang, Pidong, Martin, Nina, Sedghi, Hanie, Zhang, John, Banzal, Praseem, Fritz, Doug, Rao, Vikram, Wang, Xuezhi, Zhang, Jiageng, Patraucean, Viorica, Du, Dayou, Mordatch, Igor, Jurin, Ivan, Liu, Lewis, Dubey, Ayush, Mohan, Abhi, Nowakowski, Janek, Ion, Vlad-Doru, Wei, Nan, Tojo, Reiko, Raad, Maria Abi, Hudson, Drew A., Keshava, Vaishakh, Agrawal, Shubham, Ramirez, Kevin, Wu, Zhichun, Nguyen, Hoang, Liu, Ji, Sewak, Madhavi, Petrini, Bryce, Choi, DongHyun, Philips, Ivan, Wang, Ziyue, Bica, Ioana, Garg, Ankush, Wilkiewicz, Jarek, Agrawal, Priyanka, Guo, Danhao, Xue, Emily, Shaik, Naseer, Leach, Andrew, Khan, Sadh MNM, Wiesinger, Julia, Jerome, Sammy, Chakladar, Abhishek, Wang, Alek Wenjiao, Ornduff, Tina, Abu, Folake, Ghaffarkhah, Alireza, Wainwright, Marcus, Cortes, Mario, Liu, Frederick, Maynez, Joshua, Terzis, Andreas, Samangouei, Pouya, Mansour, Riham, Kępa, Tomasz, Aubet, François-Xavier, Algymr, Anton, Banica, Dan, Weisz, Agoston, Orban, Andras, Senges, Alexandre, Andrejczuk, Ewa, Geller, Mark, Santo, Niccolo Dal, Anklin, Valentin, Merey, Majd Al, Baeuml, Martin, Strohman, Trevor, Bai, Junwen, Petrov, Slav, Wu, Yonghui, Hassabis, Demis, Kavukcuoglu, Koray, Dean, Jeff, and Vinyals, Oriol
Subjects: Computer Science - Computation and Language, Computer Science - Artificial Intelligence
Abstract: In this report, we introduce the Gemini 1.5 family of models, representing the next generation of highly compute-efficient multimodal models capable of recalling and reasoning over fine-grained information from millions of tokens of context, including multiple long documents and hours of video and audio. The family includes two new models: (1) an updated Gemini 1.5 Pro, which exceeds the February version on the great majority of capabilities and benchmarks; (2) Gemini 1.5 Flash, a more lightweight variant designed for efficiency with minimal regression in quality. Gemini 1.5 models achieve near-perfect recall on long-context retrieval tasks across modalities, improve the state-of-the-art in long-document QA, long-video QA and long-context ASR, and match or surpass Gemini 1.0 Ultra's state-of-the-art performance across a broad set of benchmarks. Studying the limits of Gemini 1.5's long-context ability, we find continued improvement in next-token prediction and near-perfect retrieval (>99%) up to at least 10M tokens, a generational leap over existing models such as Claude 3.0 (200k) and GPT-4 Turbo (128k). Finally, we highlight real-world use cases, such as Gemini 1.5 collaborating with professionals on completing their tasks achieving 26 to 75% time savings across 10 different job categories, as well as surprising new capabilities of large language models at the frontier; when given a grammar manual for Kalamang, a language with fewer than 200 speakers worldwide, the model learns to translate English to Kalamang at a similar level to a person who learned from the same content.
Published: 2024

12. Water availability and proximity to natural areas influence plant and terrestrial invertebrate communities in urban stormwater basins and ponds

Author: Petit-Prost, Matisse, Poulin, Monique, Desrochers, André, and Lavoie, Isabelle
Published: 2024
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13. Hematological features and alternate diagnoses in critically ill thrombotic antiphospholipid syndrome patients

Author: Azoulay, Levi-Dan, Frapard, Thomas, Larcher, Romaric, Pène, Frédéric, Argaud, Laurent, Mayaux, Julien, Jamme, Matthieu, Coudroy, Remi, Mathian, Alexis, Gibelin, Aude, Azoulay, Elie, Tandjaoui-Lambiotte, Yacine, Dargent, Auguste, Beloncle, François-Michel, Raphalen, Jean-Herlé, Bréchot, Nicolas, de Prost, Nicolas, Devaquet, Jérôme, Contou, Damien, Gaugain, Samuel, Trouiller, Pierre, Grangé, Steven, Ledochowski, Stanislas, Lemarie, Jérémie, Faguer, Stanislas, Degos, Vincent, Frere, Corinne, Quentric, Paul, Moyon, Quentin, Luyt, Charles-Edouard, Combes, Alain, Amoura, Zahir, and Pineton de Chambrun, Marc
Published: 2024
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14. Houselessness, Sexual Orientation, and Mental Health Among Adults in United States Prisons

Author: Srivastava, Ankur, Rhoades, Harmony, Prost, Stephanie Grace, and Hall, William J.
Published: 2024
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15. Plug-and-Play image restoration with Stochastic deNOising REgularization

Author: Renaud, Marien, Prost, Jean, Leclaire, Arthur, and Papadakis, Nicolas
Subjects: Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning, Statistics - Machine Learning
Abstract: Plug-and-Play (PnP) algorithms are a class of iterative algorithms that address image inverse problems by combining a physical model and a deep neural network for regularization. Even if they produce impressive image restoration results, these algorithms rely on a non-standard use of a denoiser on images that are less and less noisy along the iterations, which contrasts with recent algorithms based on Diffusion Models (DM), where the denoiser is applied only on re-noised images. We propose a new PnP framework, called Stochastic deNOising REgularization (SNORE), which applies the denoiser only on images with noise of the adequate level. It is based on an explicit stochastic regularization, which leads to a stochastic gradient descent algorithm to solve ill-posed inverse problems. A convergence analysis of this algorithm and its annealing extension is provided. Experimentally, we prove that SNORE is competitive with respect to state-of-the-art methods on deblurring and inpainting tasks, both quantitatively and qualitatively.
Published: 2024

16. THz to far-infrared spectra of the known crystal polymorphs of Phenylalanine

Author: Niehaus, Thomas A., Prost, Emilien, Loriot, Vincent, Lépine, Franck, Bergé, Luc, and Skupin, Stefan
Subjects: Physics - Chemical Physics, Condensed Matter - Materials Science
Abstract: There is renewed interest in the structure of the essential amino acid Phenylalanine in the solid state. Three new polymorphs were found in the years 2012 to 2014. Here, we investigate the structure, stability, and energetical ordering of these phases using first-principles simulations at the level of Density Functional Theory incorporating van-der-Waals interactions. Two of the distinct crystal forms are found to be structurally similar and energetically very close after vibrational free energy corrections have been taken into account. Infrared absorption spectra are likewise calculated and compared to experimental measurements. By combining measurements obtained with a commercial Fourier Transform Infra-Red spectrometer and a homemade air-photonics-based THz Time Domain spectrometer, we could carry out this comparison in the vibrational frequency region from 1 to 40~THz. The excellent agreement of the line positions and the established energy ranking allow us to identify the most stable polymorph of Phenylalanine.
Published: 2024
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17. Quantitative comparison of cell-cell detachment force in different experimental setups

Author: Vishen, Amit Singh, Prost, Jacques, and Sens, Pierre
Subjects: Physics - Biological Physics, Condensed Matter - Soft Condensed Matter, Quantitative Biology - Quantitative Methods
Abstract: We compare three different setups for measuring cell-cell adhesion. We show that the measured strength depends on the type of setup that is used. For identical cells different assays measure different detachment forces. This can be understood from the fact that cell-cell detachment is a global property of the system. We also analyse the role of external force and line tension on contact angle and cell-cell detachment. Comparison with experiment suggests that the current data are essentially dynamical in nature. We dedicate this article to Fyl Pincus who for many of us is an example to be followed not only for outstanding science but also for a marvelous human behavior., Comment: 7 pages, 5 figures
Published: 2023

18. Gemini: A Family of Highly Capable Multimodal Models

Author: Gemini Team, Anil, Rohan, Borgeaud, Sebastian, Alayrac, Jean-Baptiste, Yu, Jiahui, Soricut, Radu, Schalkwyk, Johan, Dai, Andrew M., Hauth, Anja, Millican, Katie, Silver, David, Johnson, Melvin, Antonoglou, Ioannis, Schrittwieser, Julian, Glaese, Amelia, Chen, Jilin, Pitler, Emily, Lillicrap, Timothy, Lazaridou, Angeliki, Firat, Orhan, Molloy, James, Isard, Michael, Barham, Paul R., Hennigan, Tom, Lee, Benjamin, Viola, Fabio, Reynolds, Malcolm, Xu, Yuanzhong, Doherty, Ryan, Collins, Eli, Meyer, Clemens, Rutherford, Eliza, Moreira, Erica, Ayoub, Kareem, Goel, Megha, Krawczyk, Jack, Du, Cosmo, Chi, Ed, Cheng, Heng-Tze, Ni, Eric, Shah, Purvi, Kane, Patrick, Chan, Betty, Faruqui, Manaal, Severyn, Aliaksei, Lin, Hanzhao, Li, YaGuang, Cheng, Yong, Ittycheriah, Abe, Mahdieh, Mahdis, Chen, Mia, Sun, Pei, Tran, Dustin, Bagri, Sumit, Lakshminarayanan, Balaji, Liu, Jeremiah, Orban, Andras, Güra, Fabian, Zhou, Hao, Song, Xinying, Boffy, Aurelien, Ganapathy, Harish, Zheng, Steven, Choe, HyunJeong, Weisz, Ágoston, Zhu, Tao, Lu, Yifeng, Gopal, Siddharth, Kahn, Jarrod, Kula, Maciej, Pitman, Jeff, Shah, Rushin, Taropa, Emanuel, Merey, Majd Al, Baeuml, Martin, Chen, Zhifeng, Shafey, Laurent El, Zhang, Yujing, Sercinoglu, Olcan, Tucker, George, Piqueras, Enrique, Krikun, Maxim, Barr, Iain, Savinov, Nikolay, Danihelka, Ivo, Roelofs, Becca, White, Anaïs, Andreassen, Anders, von Glehn, Tamara, Yagati, Lakshman, Kazemi, Mehran, Gonzalez, Lucas, Khalman, Misha, Sygnowski, Jakub, Frechette, Alexandre, Smith, Charlotte, Culp, Laura, Proleev, Lev, Luan, Yi, Chen, Xi, Lottes, James, Schucher, Nathan, Lebron, Federico, Rrustemi, Alban, Clay, Natalie, Crone, Phil, Kocisky, Tomas, Zhao, Jeffrey, Perz, Bartek, Yu, Dian, Howard, Heidi, Bloniarz, Adam, Rae, Jack W., Lu, Han, Sifre, Laurent, Maggioni, Marcello, Alcober, Fred, Garrette, Dan, Barnes, Megan, Thakoor, Shantanu, Austin, Jacob, Barth-Maron, Gabriel, Wong, William, Joshi, Rishabh, Chaabouni, Rahma, Fatiha, Deeni, Ahuja, Arun, Tomar, Gaurav Singh, Senter, Evan, Chadwick, Martin, Kornakov, Ilya, Attaluri, Nithya, Iturrate, Iñaki, Liu, Ruibo, Li, Yunxuan, Cogan, Sarah, Chen, Jeremy, Jia, Chao, Gu, Chenjie, Zhang, Qiao, Grimstad, Jordan, Hartman, Ale Jakse, Garcia, Xavier, Pillai, Thanumalayan Sankaranarayana, Devlin, Jacob, Laskin, Michael, Casas, Diego de Las, Valter, Dasha, Tao, Connie, Blanco, Lorenzo, Badia, Adrià Puigdomènech, Reitter, David, Chen, Mianna, Brennan, Jenny, Rivera, Clara, Brin, Sergey, Iqbal, Shariq, Surita, Gabriela, Labanowski, Jane, Rao, Abhi, Winkler, Stephanie, Parisotto, Emilio, Gu, Yiming, Olszewska, Kate, Addanki, Ravi, Miech, Antoine, Louis, Annie, Teplyashin, Denis, Brown, Geoff, Catt, Elliot, Balaguer, Jan, Xiang, Jackie, Wang, Pidong, Ashwood, Zoe, Briukhov, Anton, Webson, Albert, Ganapathy, Sanjay, Sanghavi, Smit, Kannan, Ajay, Chang, Ming-Wei, Stjerngren, Axel, Djolonga, Josip, Sun, Yuting, Bapna, Ankur, Aitchison, Matthew, Pejman, Pedram, Michalewski, Henryk, Yu, Tianhe, Wang, Cindy, Love, Juliette, Ahn, Junwhan, Bloxwich, Dawn, Han, Kehang, Humphreys, Peter, Sellam, Thibault, Bradbury, James, Godbole, Varun, Samangooei, Sina, Damoc, Bogdan, Kaskasoli, Alex, Arnold, Sébastien M. R., Vasudevan, Vijay, Agrawal, Shubham, Riesa, Jason, Lepikhin, Dmitry, Tanburn, Richard, Srinivasan, Srivatsan, Lim, Hyeontaek, Hodkinson, Sarah, Shyam, Pranav, Ferret, Johan, Hand, Steven, Garg, Ankush, Paine, Tom Le, Li, Jian, Li, Yujia, Giang, Minh, Neitz, Alexander, Abbas, Zaheer, York, Sarah, Reid, Machel, Cole, Elizabeth, Chowdhery, Aakanksha, Das, Dipanjan, Rogozińska, Dominika, Nikolaev, Vitaliy, Sprechmann, Pablo, Nado, Zachary, Zilka, Lukas, Prost, Flavien, He, Luheng, Monteiro, Marianne, Mishra, Gaurav, Welty, Chris, Newlan, Josh, Jia, Dawei, Allamanis, Miltiadis, Hu, Clara Huiyi, de Liedekerke, Raoul, Gilmer, Justin, Saroufim, Carl, Rijhwani, Shruti, Hou, Shaobo, Shrivastava, Disha, Baddepudi, Anirudh, Goldin, Alex, Ozturel, Adnan, Cassirer, Albin, Xu, Yunhan, Sohn, Daniel, Sachan, Devendra, Amplayo, Reinald Kim, Swanson, Craig, Petrova, Dessie, Narayan, Shashi, Guez, Arthur, Brahma, Siddhartha, Landon, Jessica, Patel, Miteyan, Zhao, Ruizhe, Villela, Kevin, Wang, Luyu, Jia, Wenhao, Rahtz, Matthew, Giménez, Mai, Yeung, Legg, Keeling, James, Georgiev, Petko, Mincu, Diana, Wu, Boxi, Haykal, Salem, Saputro, Rachel, Vodrahalli, Kiran, Qin, James, Cankara, Zeynep, Sharma, Abhanshu, Fernando, Nick, Hawkins, Will, Neyshabur, Behnam, Kim, Solomon, Hutter, Adrian, Agrawal, Priyanka, Castro-Ros, Alex, Driessche, George van den, Wang, Tao, Yang, Fan, Chang, Shuo-yiin, Komarek, Paul, McIlroy, Ross, Lučić, Mario, Zhang, Guodong, Farhan, Wael, Sharman, Michael, Natsev, Paul, Michel, Paul, Bansal, Yamini, Qiao, Siyuan, Cao, Kris, Shakeri, Siamak, Butterfield, Christina, Chung, Justin, Rubenstein, Paul Kishan, Agrawal, Shivani, Mensch, Arthur, Soparkar, Kedar, Lenc, Karel, Chung, Timothy, Pope, Aedan, Maggiore, Loren, Kay, Jackie, Jhakra, Priya, Wang, Shibo, Maynez, Joshua, Phuong, Mary, Tobin, Taylor, Tacchetti, Andrea, Trebacz, Maja, Robinson, Kevin, Katariya, Yash, Riedel, Sebastian, Bailey, Paige, Xiao, Kefan, Ghelani, Nimesh, Aroyo, Lora, Slone, Ambrose, Houlsby, Neil, Xiong, Xuehan, Yang, Zhen, Gribovskaya, Elena, Adler, Jonas, Wirth, Mateo, Lee, Lisa, Li, Music, Kagohara, Thais, Pavagadhi, Jay, Bridgers, Sophie, Bortsova, Anna, Ghemawat, Sanjay, Ahmed, Zafarali, Liu, Tianqi, Powell, Richard, Bolina, Vijay, Iinuma, Mariko, Zablotskaia, Polina, Besley, James, Chung, Da-Woon, Dozat, Timothy, Comanescu, Ramona, Si, Xiance, Greer, Jeremy, Su, Guolong, Polacek, Martin, Kaufman, Raphaël Lopez, Tokumine, Simon, Hu, Hexiang, Buchatskaya, Elena, Miao, Yingjie, Elhawaty, Mohamed, Siddhant, Aditya, Tomasev, Nenad, Xing, Jinwei, Greer, Christina, Miller, Helen, Ashraf, Shereen, Roy, Aurko, Zhang, Zizhao, Ma, Ada, Filos, Angelos, Besta, Milos, Blevins, Rory, Klimenko, Ted, Yeh, Chih-Kuan, Changpinyo, Soravit, Mu, Jiaqi, Chang, Oscar, Pajarskas, Mantas, Muir, Carrie, Cohen, Vered, Lan, Charline Le, Haridasan, Krishna, Marathe, Amit, Hansen, Steven, Douglas, Sholto, Samuel, Rajkumar, Wang, Mingqiu, Austin, Sophia, Lan, Chang, Jiang, Jiepu, Chiu, Justin, Lorenzo, Jaime Alonso, Sjösund, Lars Lowe, Cevey, Sébastien, Gleicher, Zach, Avrahami, Thi, Boral, Anudhyan, Srinivasan, Hansa, Selo, Vittorio, May, Rhys, Aisopos, Konstantinos, Hussenot, Léonard, Soares, Livio Baldini, Baumli, Kate, Chang, Michael B., Recasens, Adrià, Caine, Ben, Pritzel, Alexander, Pavetic, Filip, Pardo, Fabio, Gergely, Anita, Frye, Justin, Ramasesh, Vinay, Horgan, Dan, Badola, Kartikeya, Kassner, Nora, Roy, Subhrajit, Dyer, Ethan, Campos, Víctor Campos, Tomala, Alex, Tang, Yunhao, Badawy, Dalia El, White, Elspeth, Mustafa, Basil, Lang, Oran, Jindal, Abhishek, Vikram, Sharad, Gong, Zhitao, Caelles, Sergi, Hemsley, Ross, Thornton, Gregory, Feng, Fangxiaoyu, Stokowiec, Wojciech, Zheng, Ce, Thacker, Phoebe, Ünlü, Çağlar, Zhang, Zhishuai, Saleh, Mohammad, Svensson, James, Bileschi, Max, Patil, Piyush, Anand, Ankesh, Ring, Roman, Tsihlas, Katerina, Vezer, Arpi, Selvi, Marco, Shevlane, Toby, Rodriguez, Mikel, Kwiatkowski, Tom, Daruki, Samira, Rong, Keran, Dafoe, Allan, FitzGerald, Nicholas, Gu-Lemberg, Keren, Khan, Mina, Hendricks, Lisa Anne, Pellat, Marie, Feinberg, Vladimir, Cobon-Kerr, James, Sainath, Tara, Rauh, Maribeth, Hashemi, Sayed Hadi, Ives, Richard, Hasson, Yana, Noland, Eric, Cao, Yuan, Byrd, Nathan, Hou, Le, Wang, Qingze, Sottiaux, Thibault, Paganini, Michela, Lespiau, Jean-Baptiste, Moufarek, Alexandre, Hassan, Samer, Shivakumar, Kaushik, van Amersfoort, Joost, Mandhane, Amol, Joshi, Pratik, Goyal, Anirudh, Tung, Matthew, Brock, Andrew, Sheahan, Hannah, Misra, Vedant, Li, Cheng, Rakićević, Nemanja, Dehghani, Mostafa, Liu, Fangyu, Mittal, Sid, Oh, Junhyuk, Noury, Seb, Sezener, Eren, Huot, Fantine, Lamm, Matthew, De Cao, Nicola, Chen, Charlie, Mudgal, Sidharth, Stella, Romina, Brooks, Kevin, Vasudevan, Gautam, Liu, Chenxi, Chain, Mainak, Melinkeri, Nivedita, Cohen, Aaron, Wang, Venus, Seymore, Kristie, Zubkov, Sergey, Goel, Rahul, Yue, Summer, Krishnakumaran, Sai, Albert, Brian, Hurley, Nate, Sano, Motoki, Mohananey, Anhad, Joughin, Jonah, Filonov, Egor, Kępa, Tomasz, Eldawy, Yomna, Lim, Jiawern, Rishi, Rahul, Badiezadegan, Shirin, Bos, Taylor, Chang, Jerry, Jain, Sanil, Padmanabhan, Sri Gayatri Sundara, Puttagunta, Subha, Krishna, Kalpesh, Baker, Leslie, Kalb, Norbert, Bedapudi, Vamsi, Kurzrok, Adam, Lei, Shuntong, Yu, Anthony, Litvin, Oren, Zhou, Xiang, Wu, Zhichun, Sobell, Sam, Siciliano, Andrea, Papir, Alan, Neale, Robby, Bragagnolo, Jonas, Toor, Tej, Chen, Tina, Anklin, Valentin, Wang, Feiran, Feng, Richie, Gholami, Milad, Ling, Kevin, Liu, Lijuan, Walter, Jules, Moghaddam, Hamid, Kishore, Arun, Adamek, Jakub, Mercado, Tyler, Mallinson, Jonathan, Wandekar, Siddhinita, Cagle, Stephen, Ofek, Eran, Garrido, Guillermo, Lombriser, Clemens, Mukha, Maksim, Sun, Botu, Mohammad, Hafeezul Rahman, Matak, Josip, Qian, Yadi, Peswani, Vikas, Janus, Pawel, Yuan, Quan, Schelin, Leif, David, Oana, Garg, Ankur, He, Yifan, Duzhyi, Oleksii, Älgmyr, Anton, Lottaz, Timothée, Li, Qi, Yadav, Vikas, Xu, Luyao, Chinien, Alex, Shivanna, Rakesh, Chuklin, Aleksandr, Li, Josie, Spadine, Carrie, Wolfe, Travis, Mohamed, Kareem, Das, Subhabrata, Dai, Zihang, He, Kyle, von Dincklage, Daniel, Upadhyay, Shyam, Maurya, Akanksha, Chi, Luyan, Krause, Sebastian, Salama, Khalid, Rabinovitch, Pam G, M, Pavan Kumar Reddy, Selvan, Aarush, Dektiarev, Mikhail, Ghiasi, Golnaz, Guven, Erdem, Gupta, Himanshu, Liu, Boyi, Sharma, Deepak, Shtacher, Idan Heimlich, Paul, Shachi, Akerlund, Oscar, Aubet, François-Xavier, Huang, Terry, Zhu, Chen, Zhu, Eric, Teixeira, Elico, Fritze, Matthew, Bertolini, Francesco, Marinescu, Liana-Eleonora, Bölle, Martin, Paulus, Dominik, Gupta, Khyatti, Latkar, Tejasi, Chang, Max, Sanders, Jason, Wilson, Roopa, Wu, Xuewei, Tan, Yi-Xuan, Thiet, Lam Nguyen, Doshi, Tulsee, Lall, Sid, Mishra, Swaroop, Chen, Wanming, Luong, Thang, Benjamin, Seth, Lee, Jasmine, Andrejczuk, Ewa, Rabiej, Dominik, Ranjan, Vipul, Styrc, Krzysztof, Yin, Pengcheng, Simon, Jon, Harriott, Malcolm Rose, Bansal, Mudit, Robsky, Alexei, Bacon, Geoff, Greene, David, Mirylenka, Daniil, Zhou, Chen, Sarvana, Obaid, Goyal, Abhimanyu, Andermatt, Samuel, Siegler, Patrick, Horn, Ben, Israel, Assaf, Pongetti, Francesco, Chen, Chih-Wei "Louis", Selvatici, Marco, Silva, Pedro, Wang, Kathie, Tolins, Jackson, Guu, Kelvin, Yogev, Roey, Cai, Xiaochen, Agostini, Alessandro, Shah, Maulik, Nguyen, Hung, Donnaile, Noah Ó, Pereira, Sébastien, Friso, Linda, Stambler, Adam, Kuang, Chenkai, Romanikhin, Yan, Geller, Mark, Yan, ZJ, Jang, Kane, Lee, Cheng-Chun, Fica, Wojciech, Malmi, Eric, Tan, Qijun, Banica, Dan, Balle, Daniel, Pham, Ryan, Huang, Yanping, Avram, Diana, Shi, Hongzhi, Singh, Jasjot, Hidey, Chris, Ahuja, Niharika, Saxena, Pranab, Dooley, Dan, Potharaju, Srividya Pranavi, O'Neill, Eileen, Gokulchandran, Anand, Foley, Ryan, Zhao, Kai, Dusenberry, Mike, Liu, Yuan, Mehta, Pulkit, Kotikalapudi, Ragha, Safranek-Shrader, Chalence, Goodman, Andrew, Kessinger, Joshua, Globen, Eran, Kolhar, Prateek, Gorgolewski, Chris, Ibrahim, Ali, Song, Yang, Eichenbaum, Ali, Brovelli, Thomas, Potluri, Sahitya, Lahoti, Preethi, Baetu, Cip, Ghorbani, Ali, Chen, Charles, Crawford, Andy, Pal, Shalini, Sridhar, Mukund, Gurita, Petru, Mujika, Asier, Petrovski, Igor, Cedoz, Pierre-Louis, Li, Chenmei, Chen, Shiyuan, Santo, Niccolò Dal, Goyal, Siddharth, Punjabi, Jitesh, Kappaganthu, Karthik, Kwak, Chester, LV, Pallavi, Velury, Sarmishta, Choudhury, Himadri, Hall, Jamie, Shah, Premal, Figueira, Ricardo, Thomas, Matt, Lu, Minjie, Zhou, Ting, Kumar, Chintu, Jurdi, Thomas, Chikkerur, Sharat, Ma, Yenai, Yu, Adams, Kwak, Soo, Ähdel, Victor, Rajayogam, Sujeevan, Choma, Travis, Liu, Fei, Barua, Aditya, Ji, Colin, Park, Ji Ho, Hellendoorn, Vincent, Bailey, Alex, Bilal, Taylan, Zhou, Huanjie, Khatir, Mehrdad, Sutton, Charles, Rzadkowski, Wojciech, Macintosh, Fiona, Shagin, Konstantin, Medina, Paul, Liang, Chen, Zhou, Jinjing, Shah, Pararth, Bi, Yingying, Dankovics, Attila, Banga, Shipra, Lehmann, Sabine, Bredesen, Marissa, Lin, Zifan, Hoffmann, John Eric, Lai, Jonathan, Chung, Raynald, Yang, Kai, Balani, Nihal, Bražinskas, Arthur, Sozanschi, Andrei, Hayes, Matthew, Alcalde, Héctor Fernández, Makarov, Peter, Chen, Will, Stella, Antonio, Snijders, Liselotte, Mandl, Michael, Kärrman, Ante, Nowak, Paweł, Wu, Xinyi, Dyck, Alex, Vaidyanathan, Krishnan, R, Raghavender, Mallet, Jessica, Rudominer, Mitch, Johnston, Eric, Mittal, Sushil, Udathu, Akhil, Christensen, Janara, Verma, Vishal, Irving, Zach, Santucci, Andreas, Elsayed, Gamaleldin, Davoodi, Elnaz, Georgiev, Marin, Tenney, Ian, Hua, Nan, Cideron, Geoffrey, Leurent, Edouard, Alnahlawi, Mahmoud, Georgescu, Ionut, Wei, Nan, Zheng, Ivy, Scandinaro, Dylan, Jiang, Heinrich, Snoek, Jasper, Sundararajan, Mukund, Wang, Xuezhi, Ontiveros, Zack, Karo, Itay, Cole, Jeremy, Rajashekhar, Vinu, Tumeh, Lara, Ben-David, Eyal, Jain, Rishub, Uesato, Jonathan, Datta, Romina, Bunyan, Oskar, Wu, Shimu, Zhang, John, Stanczyk, Piotr, Zhang, Ye, Steiner, David, Naskar, Subhajit, Azzam, Michael, Johnson, Matthew, Paszke, Adam, Chiu, Chung-Cheng, Elias, Jaume Sanchez, Mohiuddin, Afroz, Muhammad, Faizan, Miao, Jin, Lee, Andrew, Vieillard, Nino, Park, Jane, Zhang, Jiageng, Stanway, Jeff, Garmon, Drew, Karmarkar, Abhijit, Dong, Zhe, Lee, Jong, Kumar, Aviral, Zhou, Luowei, Evens, Jonathan, Isaac, William, Irving, Geoffrey, Loper, Edward, Fink, Michael, Arkatkar, Isha, Chen, Nanxin, Shafran, Izhak, Petrychenko, Ivan, Chen, Zhe, Jia, Johnson, Levskaya, Anselm, Zhu, Zhenkai, Grabowski, Peter, Mao, Yu, Magni, Alberto, Yao, Kaisheng, Snaider, Javier, Casagrande, Norman, Palmer, Evan, Suganthan, Paul, Castaño, Alfonso, Giannoumis, Irene, Kim, Wooyeol, Rybiński, Mikołaj, Sreevatsa, Ashwin, Prendki, Jennifer, Soergel, David, Goedeckemeyer, Adrian, Gierke, Willi, Jafari, Mohsen, Gaba, Meenu, Wiesner, Jeremy, Wright, Diana Gage, Wei, Yawen, Vashisht, Harsha, Kulizhskaya, Yana, Hoover, Jay, Le, Maigo, Li, Lu, Iwuanyanwu, Chimezie, Liu, Lu, Ramirez, Kevin, Khorlin, Andrey, Cui, Albert, LIN, Tian, Wu, Marcus, Aguilar, Ricardo, Pallo, Keith, Chakladar, Abhishek, Perng, Ginger, Abellan, Elena Allica, Zhang, Mingyang, Dasgupta, Ishita, Kushman, Nate, Penchev, Ivo, Repina, Alena, Wu, Xihui, van der Weide, Tom, Ponnapalli, Priya, Kaplan, Caroline, Simsa, Jiri, Li, Shuangfeng, Dousse, Olivier, Piper, Jeff, Ie, Nathan, Pasumarthi, Rama, Lintz, Nathan, Vijayakumar, Anitha, Andor, Daniel, Valenzuela, Pedro, Lui, Minnie, Paduraru, Cosmin, Peng, Daiyi, Lee, Katherine, Zhang, Shuyuan, Greene, Somer, Nguyen, Duc Dung, Kurylowicz, Paula, Hardin, Cassidy, Dixon, Lucas, Janzer, Lili, Choo, Kiam, Feng, Ziqiang, Zhang, Biao, Singhal, Achintya, Du, Dayou, McKinnon, Dan, Antropova, Natasha, Bolukbasi, Tolga, Keller, Orgad, Reid, David, Finchelstein, Daniel, Raad, Maria Abi, Crocker, Remi, Hawkins, Peter, Dadashi, Robert, Gaffney, Colin, Franko, Ken, Bulanova, Anna, Leblond, Rémi, Chung, Shirley, Askham, Harry, Cobo, Luis C., Xu, Kelvin, Fischer, Felix, Xu, Jun, Sorokin, Christina, Alberti, Chris, Lin, Chu-Cheng, Evans, Colin, Dimitriev, Alek, Forbes, Hannah, Banarse, Dylan, Tung, Zora, Omernick, Mark, Bishop, Colton, Sterneck, Rachel, Jain, Rohan, Xia, Jiawei, Amid, Ehsan, Piccinno, Francesco, Wang, Xingyu, Banzal, Praseem, Mankowitz, Daniel J., Polozov, Alex, Krakovna, Victoria, Brown, Sasha, Bateni, MohammadHossein, Duan, Dennis, Firoiu, Vlad, Thotakuri, Meghana, Natan, Tom, Geist, Matthieu, Girgin, Ser tan, Li, Hui, Ye, Jiayu, Roval, Ofir, Tojo, Reiko, Kwong, Michael, Lee-Thorp, James, Yew, Christopher, Sinopalnikov, Danila, Ramos, Sabela, Mellor, John, Sharma, Abhishek, Wu, Kathy, Miller, David, Sonnerat, Nicolas, Vnukov, Denis, Greig, Rory, Beattie, Jennifer, Caveness, Emily, Bai, Libin, Eisenschlos, Julian, Korchemniy, Alex, Tsai, Tomy, Jasarevic, Mimi, Kong, Weize, Dao, Phuong, Zheng, Zeyu, Liu, Frederick, Zhu, Rui, Teh, Tian Huey, Sanmiya, Jason, Gladchenko, Evgeny, Trdin, Nejc, Toyama, Daniel, Rosen, Evan, Tavakkol, Sasan, Xue, Linting, Elkind, Chen, Woodman, Oliver, Carpenter, John, Papamakarios, George, Kemp, Rupert, Kafle, Sushant, Grunina, Tanya, Sinha, Rishika, Talbert, Alice, Wu, Diane, Owusu-Afriyie, Denese, Thornton, Chloe, Pont-Tuset, Jordi, Narayana, Pradyumna, Li, Jing, Fatehi, Saaber, Wieting, John, Ajmeri, Omar, Uria, Benigno, Ko, Yeongil, Knight, Laura, Héliou, Amélie, Niu, Ning, Gu, Shane, Pang, Chenxi, Li, Yeqing, Levine, Nir, Stolovich, Ariel, Santamaria-Fernandez, Rebeca, Goenka, Sonam, Yustalim, Wenny, Strudel, Robin, Elqursh, Ali, Deck, Charlie, Lee, Hyo, Li, Zonglin, Levin, Kyle, Hoffmann, Raphael, Holtmann-Rice, Dan, Bachem, Olivier, Arora, Sho, Koh, Christy, Yeganeh, Soheil Hassas, Põder, Siim, Tariq, Mukarram, Sun, Yanhua, Ionita, Lucian, Seyedhosseini, Mojtaba, Tafti, Pouya, Liu, Zhiyu, Gulati, Anmol, Liu, Jasmine, Ye, Xinyu, Chrzaszcz, Bart, Wang, Lily, Sethi, Nikhil, Li, Tianrun, Brown, Ben, Singh, Shreya, Fan, Wei, Parisi, Aaron, Stanton, Joe, Koverkathu, Vinod, Choquette-Choo, Christopher A., Li, Yunjie, Lu, TJ, Shroff, Prakash, Varadarajan, Mani, Bahargam, Sanaz, Willoughby, Rob, Gaddy, David, Desjardins, Guillaume, Cornero, Marco, Robenek, Brona, Mittal, Bhavishya, Albrecht, Ben, Shenoy, Ashish, Moiseev, Fedor, Jacobsson, Henrik, Ghaffarkhah, Alireza, Rivière, Morgane, Walton, Alanna, Crepy, Clément, Parrish, Alicia, Zhou, Zongwei, Farabet, Clement, Radebaugh, Carey, Srinivasan, Praveen, van der Salm, Claudia, Fidjeland, Andreas, Scellato, Salvatore, Latorre-Chimoto, Eri, Klimczak-Plucińska, Hanna, Bridson, David, de Cesare, Dario, Hudson, Tom, Mendolicchio, Piermaria, Walker, Lexi, Morris, Alex, Mauger, Matthew, Guseynov, Alexey, Reid, Alison, Odoom, Seth, Loher, Lucia, Cotruta, Victor, Yenugula, Madhavi, Grewe, Dominik, Petrushkina, Anastasia, Duerig, Tom, Sanchez, Antonio, Yadlowsky, Steve, Shen, Amy, Globerson, Amir, Webb, Lynette, Dua, Sahil, Li, Dong, Bhupatiraju, Surya, Hurt, Dan, Qureshi, Haroon, Agarwal, Ananth, Shani, Tomer, Eyal, Matan, Khare, Anuj, Belle, Shreyas Rammohan, Wang, Lei, Tekur, Chetan, Kale, Mihir Sanjay, Wei, Jinliang, Sang, Ruoxin, Saeta, Brennan, Liechty, Tyler, Sun, Yi, Zhao, Yao, Lee, Stephan, Nayak, Pandu, Fritz, Doug, Vuyyuru, Manish Reddy, Aslanides, John, Vyas, Nidhi, Wicke, Martin, Ma, Xiao, Eltyshev, Evgenii, Martin, Nina, Cate, Hardie, Manyika, James, Amiri, Keyvan, Kim, Yelin, Xiong, Xi, Kang, Kai, Luisier, Florian, Tripuraneni, Nilesh, Madras, David, Guo, Mandy, Waters, Austin, Wang, Oliver, Ainslie, Joshua, Baldridge, Jason, Zhang, Han, Pruthi, Garima, Bauer, Jakob, Yang, Feng, Mansour, Riham, Gelman, Jason, Xu, Yang, Polovets, George, Liu, Ji, Cai, Honglong, Chen, Warren, Sheng, XiangHai, Xue, Emily, Ozair, Sherjil, Angermueller, Christof, Li, Xiaowei, Sinha, Anoop, Wang, Weiren, Wiesinger, Julia, Koukoumidis, Emmanouil, Tian, Yuan, Iyer, Anand, Gurumurthy, Madhu, Goldenson, Mark, Shah, Parashar, Blake, MK, Yu, Hongkun, Urbanowicz, Anthony, Palomaki, Jennimaria, Fernando, Chrisantha, Durden, Ken, Mehta, Harsh, Momchev, Nikola, Rahimtoroghi, Elahe, Georgaki, Maria, Raul, Amit, Ruder, Sebastian, Redshaw, Morgan, Lee, Jinhyuk, Zhou, Denny, Jalan, Komal, Li, Dinghua, Hechtman, Blake, Schuh, Parker, Nasr, Milad, Milan, Kieran, Mikulik, Vladimir, Franco, Juliana, Green, Tim, Nguyen, Nam, Kelley, Joe, Mahendru, Aroma, Hu, Andrea, Howland, Joshua, Vargas, Ben, Hui, Jeffrey, Bansal, Kshitij, Rao, Vikram, Ghiya, Rakesh, Wang, Emma, Ye, Ke, Sarr, Jean Michel, Preston, Melanie Moranski, Elish, Madeleine, Li, Steve, Kaku, Aakash, Gupta, Jigar, Pasupat, Ice, Juan, Da-Cheng, Someswar, Milan, M., Tejvi, Chen, Xinyun, Amini, Aida, Fabrikant, Alex, Chu, Eric, Dong, Xuanyi, Muthal, Amruta, Buthpitiya, Senaka, Jauhari, Sarthak, Khandelwal, Urvashi, Hitron, Ayal, Ren, Jie, Rinaldi, Larissa, Drath, Shahar, Dabush, Avigail, Jiang, Nan-Jiang, Godhia, Harshal, Sachs, Uli, Chen, Anthony, Fan, Yicheng, Taitelbaum, Hagai, Noga, Hila, Dai, Zhuyun, Wang, James, Hamer, Jenny, Ferng, Chun-Sung, Elkind, Chenel, Atias, Aviel, Lee, Paulina, Listík, Vít, Carlen, Mathias, van de Kerkhof, Jan, Pikus, Marcin, Zaher, Krunoslav, Müller, Paul, Zykova, Sasha, Stefanec, Richard, Gatsko, Vitaly, Hirnschall, Christoph, Sethi, Ashwin, Xu, Xingyu Federico, Ahuja, Chetan, Tsai, Beth, Stefanoiu, Anca, Feng, Bo, Dhandhania, Keshav, Katyal, Manish, Gupta, Akshay, Parulekar, Atharva, Pitta, Divya, Zhao, Jing, Bhatia, Vivaan, Bhavnani, Yashodha, Alhadlaq, Omar, Li, Xiaolin, Danenberg, Peter, Tu, Dennis, Pine, Alex, Filippova, Vera, Ghosh, Abhipso, Limonchik, Ben, Urala, Bhargava, Lanka, Chaitanya Krishna, Clive, Derik, Li, Edward, Wu, Hao, Hongtongsak, Kevin, Li, Ianna, Thakkar, Kalind, Omarov, Kuanysh, Majmundar, Kushal, Alverson, Michael, Kucharski, Michael, Patel, Mohak, Jain, Mudit, Zabelin, Maksim, Pelagatti, Paolo, Kohli, Rohan, Kumar, Saurabh, Kim, Joseph, Sankar, Swetha, Shah, Vineet, Ramachandruni, Lakshmi, Zeng, Xiangkai, Bariach, Ben, Weidinger, Laura, Vu, Tu, Andreev, Alek, He, Antoine, Hui, Kevin, Kashem, Sheleem, Subramanya, Amar, Hsiao, Sissie, Hassabis, Demis, Kavukcuoglu, Koray, Sadovsky, Adam, Le, Quoc, Strohman, Trevor, Wu, Yonghui, Petrov, Slav, Dean, Jeffrey, and Vinyals, Oriol
Subjects: Computer Science - Computation and Language, Computer Science - Artificial Intelligence, Computer Science - Computer Vision and Pattern Recognition
Abstract: This report introduces a new family of multimodal models, Gemini, that exhibit remarkable capabilities across image, audio, video, and text understanding. The Gemini family consists of Ultra, Pro, and Nano sizes, suitable for applications ranging from complex reasoning tasks to on-device memory-constrained use-cases. Evaluation on a broad range of benchmarks shows that our most-capable Gemini Ultra model advances the state of the art in 30 of 32 of these benchmarks - notably being the first model to achieve human-expert performance on the well-studied exam benchmark MMLU, and improving the state of the art in every one of the 20 multimodal benchmarks we examined. We believe that the new capabilities of the Gemini family in cross-modal reasoning and language understanding will enable a wide variety of use cases. We discuss our approach toward post-training and deploying Gemini models responsibly to users through services including Gemini, Gemini Advanced, Google AI Studio, and Cloud Vertex AI.
Published: 2023

19. FRAPPE: A Group Fairness Framework for Post-Processing Everything

Author: Tifrea, Alexandru, Lahoti, Preethi, Packer, Ben, Halpern, Yoni, Beirami, Ahmad, and Prost, Flavien
Subjects: Computer Science - Machine Learning, Computer Science - Computers and Society
Abstract: Despite achieving promising fairness-error trade-offs, in-processing mitigation techniques for group fairness cannot be employed in numerous practical applications with limited computation resources or no access to the training pipeline of the prediction model. In these situations, post-processing is a viable alternative. However, current methods are tailored to specific problem settings and fairness definitions and hence, are not as broadly applicable as in-processing. In this work, we propose a framework that turns any regularized in-processing method into a post-processing approach. This procedure prescribes a way to obtain post-processing techniques for a much broader range of problem settings than the prior post-processing literature. We show theoretically and through extensive experiments that our framework preserves the good fairness-error trade-offs achieved with in-processing and can improve over the effectiveness of prior post-processing methods. Finally, we demonstrate several advantages of a modular mitigation strategy that disentangles the training of the prediction model from the fairness mitigation, including better performance on tasks with partial group labels., Comment: Conference paper at ICML 2024
Published: 2023

20. Accurate quantification of dislocation loops in complex functional alloys enabled by deep learning image analysis

Author: Bilyk, Thomas, Goryaeva, Alexandra. M., Marinica, Mihai-Cosmin, Flament, Camille, Sabathier, Catherine, Leroy, Eric, Loyer-Prost, Marie, and Meslin, Estelle
Published: 2024
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21. The double-edged role of FASII regulator FabT in Streptococcus pyogenes infection

Author: Lambert, Clara, Gaillard, Marine, Wongdontree, Paprapach, Bachmann, Caroline, Hautcoeur, Antoine, Gloux, Karine, Guilbert, Thomas, Méhats, Celine, Prost, Bastien, Solgadi, Audrey, Abreu, Sonia, Andrieu, Muriel, Poyart, Claire, Gruss, Alexandra, and Fouet, Agnes
Published: 2024
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22. Surgical site infection in severe trauma patients in intensive care: epidemiology and risk factors

Author: Savio, Lucie, Simeone, Pierre, Baron, Sophie, Antonini, François, Bruder, Nicolas, Boussen, Salah, Zieleskiewicz, Laurent, Blondel, Benjamin, Prost, Solène, Baucher, Guillaume, Lebaron, Marie, Florant, Thibault, Boucekine, Mohamed, Leone, Marc, and Velly, Lionel
Published: 2024
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23. Performance and impact of rapid multiplex PCR on diagnosis and treatment of ventilated hospital-acquired pneumonia in patients with extended-spectrum β-lactamase-producing Enterobacterales rectal carriage

Author: Bay, Pierre, Fihman, Vincent, Woerther, Paul-Louis, Peiffer, Bastien, Gendreau, Ségolène, Arrestier, Romain, Labedade, Pascale, Moncomble, Elsa, Gaillet, Antoine, Carteaux, Guillaume, de Prost, Nicolas, Mekontso Dessap, Armand, and Razazi, Keyvan
Published: 2024
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24. Production, purification, and quality assessment of borrelial proteins CspZ from Borrelia burgdorferi and FhbA from Borrelia hermsii

Author: Guérin, Mickaël, Vandevenne, Marylène, Brans, Alain, Matagne, André, Marquant, Rodrigue, Prost, Elise, Octave, Stéphane, Avalle, Bérangère, Maffucci, Irene, and Padiolleau-Lefèvre, Séverine
Published: 2024
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25. COVID-19 associated pulmonary aspergillosis in critically-ill patients – authors’ reply

Author: Bay, Pierre, Audureau, Etienne, Fourati, Slim, and de Prost, Nicolas
Published: 2024
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26. Clinical phenotypes and outcomes associated with SARS-CoV-2 Omicron sublineage JN.1 in critically ill COVID-19 patients: a prospective, multicenter cohort study in France, November 2022 to January 2024

Author: de Prost, Nicolas, Audureau, Etienne, Guillon, Antoine, Handala, Lynda, Préau, Sébastien, Guigon, Aurélie, Uhel, Fabrice, Le Hingrat, Quentin, Delamaire, Flora, Grolhier, Claire, Tamion, Fabienne, Moisan, Alice, Darreau, Cédric, Thomin, Jean, Contou, Damien, Henry, Amandine, Daix, Thomas, Hantz, Sébastien, Saccheri, Clément, Giordanengo, Valérie, Pham, Tài, Chaghouri, Amal, Bay, Pierre, Pawlotsky, Jean-Michel, and Fourati, Slim
Published: 2024
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27. Distinct dynamics of mRNA LNPs in mice and nonhuman primates revealed by in vivo imaging

Author: Lemdani, Katia, Marlin, Romain, Mayet, Céline, Perkov, Vladimir, Pascal, Quentin, Ripoll, Manon, Relouzat, Francis, Dhooge, Nina, Bossevot, Laetitia, Dereuddre-Bosquet, Nathalie, Dargazanli, Gihad, Thibaut-Duprey, Kevin, Haensler, Jean, Chapon, Catherine, Prost, Christine, and Le Grand, Roger
Published: 2024
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28. Correction: COVID-19 associated pulmonary aspergillosis in critically-ill patients: a prospective multicenter study in the era of Delta and Omicron variants

Author: Bay, Pierre, Audureau, Etienne, Préau, Sébastien, Favory, Raphaël, Guigon, Aurélie, Heming, Nicholas, Gault, Elyanne, Pham, Tài, Chaghouri, Amal, Turpin, Matthieu, Morand-Joubert, Laurence, Jochmans, Sébastien, Pitsch, Aurélia, Meireles, Sylvie, Contou, Damien, Henry, Amandine, Joseph, Adrien, Chaix, Marie-Laure, Uhel, Fabrice, Roux, Damien, Descamps, Diane, Emery, Malo, Garcia-Sanchez, Claudio, Levy, David, Burrel, Sonia, Mayaux, Julien, Kimmoun, Antoine, Hartard, Cédric, Pène, Frédéric, Rozenberg, Flore, Gaudry, Stéphane, Brichler, Ségolène, Guillon, Antoine, Handala, Lynda, Tamion, Fabienne, Moisan, Alice, Daix, Thomas, Hantz, Sébastien, Delamaire, Flora, Thibault, Vincent, Souweine, Bertrand, Henquell, Cecile, Picard, Lucile, Botterel, Françoise, Rodriguez, Christophe, Dessap, Armand Mekontso, Pawlotsky, Jean-Michel, Fourati, Slim, and de Prost, Nicolas
Published: 2024
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29. Community-acquired Klebsiella pneumoniae pneumonia in ICU: a multicenter retrospective study

Author: Grosjean, Vincent, Gressens, Simon B., Pham, Tài, Gaudry, Stéphane, Ait-Oufella, Hafid, De Prost, Nicolas, Mayaux, Julien, Guerot, Emmanuel, Leflon-Guibout, Véronique, Mayer, Noémie, Bert, Frédéric, Gault, Nathalie, Massonnaud, Clément R., and Roux, Damien
Published: 2024
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30. COVID-19 associated pulmonary aspergillosis in critically-ill patients: a prospective multicenter study in the era of Delta and Omicron variants

Author: Bay, Pierre, Audureau, Etienne, Préau, Sébastien, Favory, Raphaël, Guigon, Aurélie, Heming, Nicholas, Gault, Elyanne, Pham, Tài, Chaghouri, Amal, Turpin, Matthieu, Morand-Joubert, Laurence, Jochmans, Sébastien, Pitsch, Aurélia, Meireles, Sylvie, Contou, Damien, Henry, Amandine, Joseph, Adrien, Chaix, Marie-Laure, Uhel, Fabrice, Roux, Damien, Descamps, Diane, Emery, Malo, Garcia-Sanchez, Claudio, Levy, David, Burrel, Sonia, Mayaux, Julien, Kimmoun, Antoine, Hartard, Cédric, Pène, Frédéric, Rozenberg, Flore, Gaudry, Stéphane, Brichler, Ségolène, Guillon, Antoine, Handala, Lynda, Tamion, Fabienne, Moisan, Alice, Daix, Thomas, Hantz, Sébastien, Delamaire, Flora, Thibault, Vincent, Souweine, Bertrand, Henquell, Cecile, Picard, Lucile, Botterel, Françoise, Rodriguez, Christophe, Dessap, Armand Mekontso, Pawlotsky, Jean-Michel, Fourati, Slim, and de Prost, Nicolas
Published: 2024
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31. Navigation versus fluoroscopy in minimalinvasive iliosacral screw placement

Author: Prost, Max, Taday, Roman, Beyersdorf, Carl Christoph Paul, Latz, David, Windolf, Joachim, Scheyerer, Max Joseph, and Konieczny, Markus Rafael
Published: 2024
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32. Regional pulmonary perfusion, blood volume, and their relationship change in experimental early ARDS

Author: Santos, Arnoldo, Motta-Ribeiro, Gabriel C., de Prost, Nicolas, Tucci, Mauro R., Wellman, Tyler J., Vidal Melo, Marcos F., and Winkler, Tilo
Published: 2024
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33. Diversity of selected toll-like receptor genes in cheetahs (Acinonyx jubatus) and African leopards (Panthera pardus pardus)

Author: Meißner, René, Mokgokong, Prudent, Pretorius, Chantelle, Winter, Sven, Labuschagne, Kim, Kotze, Antoinette, Prost, Stefan, Horin, Petr, Dalton, Desire, and Burger, Pamela A.
Published: 2024
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34. The Potential of Community Interactions as Inducers of Agroecological Transition: The Case of a Digital Agricultural Community

Author: Celina Slimi, Lorène Prost, Marianne Cerf, and Magali Prost
Abstract: Purpose: To study community interactions and thus to highlight potential ways to support farmers' professional transition toward more sustainable agriculture. Methodology: Mixed methods with a questionnaire, interviews, peer-to-peer interactions, and a theoretical framework to analyze drivers of indeterminacy that can trigger a break in farmers' routines. The study took place in a digital agricultural community. Findings: We highlighted three potential drivers of indeterminacy in a professional transition process like Agroecological Transition (AET), as well as the role of community facilitator. Practical implications: Integrating into farmers' training and extension services the issues of valuation to discuss how practices and objects are prised and evaluated. This can open a way for new meanings and values that support AET and support a departure from usual standards. Theoretical implications: Applying inquiry theory as an epistemic proposition to examine support for farmers' professional transitions and their training in relation to their real work situation. Originality: We propose an articulation between the study of a digital platform and the analysis of the drivers of engagement in an agroecological transition process.
Published: 2024
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35. How Could Social Media Support Farmers Concerned with Sustainability Issues?

Author: Magali Prost, Hélène Gross, and Lorène Prost
Abstract: Purpose: This article aims to contribute to building an understanding of how social media may support farmers in transition to a more sustainable agriculture. Methodology: We used a questionnaire survey and in-depth interviews with farmers concerned with sustainability issues to characterize the diversity of their social media (SM) uses and user profiles. Findings: We show widespread but also very contrasting uses of SM by farmers concerned with sustainability issues, combining epistemic and socio-emotional dimensions. Practical implications: We propose several implications for facilitators of online and in-person groups dedicated to supporting farmers engaged in sustainability transitions. Theoretical implications: The use that farmers concerned with sustainability issues make of SM supports an integrated view of farmers' transitions to sustainability as processes that are not only technical but also involve many variable dimensions. Our understanding would therefore benefit from further analyzing SM users as virtual communities of practice (COPv). Originality: Rather than focusing on one SM, we start from farmers' uses of various SM, which provides an original perspective on SM in agriculture. It also contributes to filling in the gap in knowledge about digital tools' potential contribution to sustainability.
Published: 2024
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36. Curvature-induced clustering of cell adhesion proteins

Author: Lin, Shao-Zhen, Prost, Jacques, and Rupprecht, Jean-Francois
Subjects: Condensed Matter - Soft Condensed Matter
Abstract: Cell adhesion proteins typically form stable clusters that anchor the cell membrane to its environment. Several works have suggested that cell membrane protein clusters can emerge from a local feedback between the membrane curvature and the density of proteins. Here, we investigate the effect of such curvature-sensing mechanism in the context of cell adhesion proteins. We show how clustering emerges in an intermediate range of adhesion and curvature-sensing strengths. We identify key differences with the tilt-induced gradient sensing mechanism we previously proposed (Lin et al., arXiv:2307.03670, 2023)., Comment: 13 pages, 7 figures
Published: 2023

37. A large topographic feature on the surface of the trans-Neptunian object (307261) 2002 MS$_4$ measured from stellar occultations

Author: Rommel, F. L., Braga-Ribas, F., Ortiz, J. L., Sicardy, B., Santos-Sanz, P., Desmars, J., Camargo, J. I. B., Vieira-Martins, R., Assafin, M., Morgado, B. E., Boufleur, R. C., Benedetti-Rossi, G., Gomes-Júnior, A. R., Fernández-Valenzuela, E., Holler, B. J., Souami, D., Duffard, R., Margoti, G., Vara-Lubiano, M., Lecacheux, J., Plouvier, J. L., Morales, N., Maury, A., Fabrega, J., Ceravolo, P., Jehin, E., Albanese, D., Mariey, H., Cikota, S., Ruždjak, D., Cikota, A., Szakáts, R., Aissa, D. Baba, Gringahcene, Z., Kashuba, V., Koshkin, N., Zhukov, V., Fişek, S., Çakır, O., Özer, S., Schnabel, C., Schnabel, M., Signoret, F., Morrone, L., Santana-Ros, T., Pereira, C. L., Emilio, M., Burdanov, A. Y., de Wit, J., Barkaoui, K., Gillon, M., Leto, G., Frasca, A., Catanzaro, G., Sanchez, R. Zanmar, Tagliaferri, U., Di Sora, M., Isopi, G., Krugly, Y., Slyusarev, I., Chiorny, V., Mikuž, H., Bacci, P., Maestripieri, M., Grazia, M. D., de la Cueva, I., Yuste-Moreno, M., Ciabattari, F., Kozhukhov, O. M., Serra-Ricart, M., Alarcon, M. R., Licandro, J., Masi, G., Bacci, R., Bosch, J. M., Behem, R., Prost, J. -P., Renner, S., Conjat, M., Bachini, M., Succi, G., Stoian, L., Juravle, A., Carosati, D., Gowe, B., Carrillo, J., Zheleznyak, A. P., Montigiani, N., Foster, C. R., Mannucci, M., Ruocco, N., Cuevas, F., Di Marcantonio, P., Coretti, I., Iafrate, G., Baldini, V., Collins, M., Pál, A., Csák, B., Fernández-Garcia, E., Castro-Tirado, A. J., Hudin, L., Madiedo, J. M., Anghel, R. M., Calvo-Fernández, J. F., Valvasori, A., Guido, E., Gherase, R. M., Kamoun, S., Fafet, R., Sánchez-González, M., Curelaru, L., Vîntdevară, C. D., Danescu, C. A., Gout, J. -F., Schmitz, C. J., Sota, A., Belskaya, I., Rodríguez-Marco, M., Kilic, Y., Frappa, E., Klotz, A., Lavayssière, M., Oliveira, J. Marques, Popescu, M., Mammana, L. A., Fernández-Lajús, E., Schmidt, M., Hopp, U., Komžík, R., Pribulla, T., Tomko, D., Husárik, M., Erece, O., Eryilmaz, S., Buzzi, L., Gährken, B., Nardiello, D., Hornoch, K., Sonbas, E., Er, H., Burwitz, V., Sybilski, P. Waldemar, Bykowski, W., Müller, T. G., Ogloza, W., Gonçalves, R., Ferreira, J. F., Ferreira, M., Bento, M., Meister, S., Bagiran, M. N., Tekeş, M., Marciniak, A., Moravec, Z., Delinčák, P., Gianni, G., Casalnuovo, G. B., Boutet, M., Sanchez, J., Klemt, B., Wuensche, N., Burzynski, W., Borkowski, M., Serrau, M., Dangl, G., Klös, O., Weber, C., Urbaník, M., Rousselot, L., Kubánek, J., André, P., Colazo, C., Spagnotto, J., Sickafoose, A. A., Hueso, R., Sánchez-Lavega, A., Fisher, R. S., Rengstorf, A. W., Perelló, C., Dascalu, M., Altan, M., Gazeas, K., de Santana, T., Sfair, R., Winter, O. C., Kalkan, S., Canales-Moreno, O., Trigo-Rodríguez, J. M., Tsamis, V., Tigani, K., Sioulas, N., Lekkas, G., Bertesteanu, D. N., Dumitrescu, V., Wilberger, A. J., Barnes, J. W., Fieber-Beyer, S. K., Swaney, R. L., Fuentes, C., Mendez, R. A., Dumitru, B. D., Flynn, R. L., and Wake, D. A.
Subjects: Astrophysics - Earth and Planetary Astrophysics
Abstract: This work aims at constraining the size, shape, and geometric albedo of the dwarf planet candidate 2002 MS4 through the analysis of nine stellar occultation events. Using multichord detection, we also studied the object's topography by analyzing the obtained limb and the residuals between observed chords and the best-fitted ellipse. We predicted and organized the observational campaigns of nine stellar occultations by 2002 MS4 between 2019 and 2022, resulting in two single-chord events, four double-chord detections, and three events with three to up to sixty-one positive chords. Using 13 selected chords from the 8 August 2020 event, we determined the global elliptical limb of 2002 MS4. The best-fitted ellipse, combined with the object's rotational information from the literature, constrains the object's size, shape, and albedo. Additionally, we developed a new method to characterize topography features on the object's limb. The global limb has a semi-major axis of 412 $\pm$ 10 km, a semi-minor axis of 385 $\pm$ 17 km, and the position angle of the minor axis is 121 $^\circ$ $\pm$ 16$^\circ$. From this instantaneous limb, we obtained 2002 MS4's geometric albedo and the projected area-equivalent diameter. Significant deviations from the fitted ellipse in the northernmost limb are detected from multiple sites highlighting three distinct topographic features: one 11 km depth depression followed by a 25$^{+4}_{-5}$ km height elevation next to a crater-like depression with an extension of 322 $\pm$ 39 km and 45.1 $\pm$ 1.5 km deep. Our results present an object that is $\approx$138 km smaller in diameter than derived from thermal data, possibly indicating the presence of a so-far unknown satellite. However, within the error bars, the geometric albedo in the V-band agrees with the results published in the literature, even with the radiometric-derived albedo.
Published: 2023
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38. Towards A Scalable Solution for Improving Multi-Group Fairness in Compositional Classification

Author: Atwood, James, Tian, Tina, Packer, Ben, Deodhar, Meghana, Chen, Jilin, Beutel, Alex, Prost, Flavien, and Beirami, Ahmad
Subjects: Computer Science - Machine Learning, Computer Science - Artificial Intelligence, Computer Science - Computers and Society
Abstract: Despite the rich literature on machine learning fairness, relatively little attention has been paid to remediating complex systems, where the final prediction is the combination of multiple classifiers and where multiple groups are present. In this paper, we first show that natural baseline approaches for improving equal opportunity fairness scale linearly with the product of the number of remediated groups and the number of remediated prediction labels, rendering them impractical. We then introduce two simple techniques, called {\em task-overconditioning} and {\em group-interleaving}, to achieve a constant scaling in this multi-group multi-label setup. Our experimental results in academic and real-world environments demonstrate the effectiveness of our proposal at mitigation within this environment.
Published: 2023

39. Tilt-induced clustering of cell adhesion proteins

Author: Lin, Shao-Zhen, Changede, Rishita, Sheetz, Michael P., Prost, Jacques, and Rupprecht, Jean-Francois
Subjects: Condensed Matter - Soft Condensed Matter, Physics - Biological Physics
Abstract: Cell adhesion proteins are transmembrane proteins that bind cells to their environment. These proteins typically cluster into disk-shaped or linear structures. Here we show that such clustering patterns spontaneously emerge when the protein sense the membrane deformation gradient, for example by reaching a lower-energy conformation when the membrane is tilted relative to the underlying binding substrate. Increasing the strength of the membrane gradient-sensing mechanism first yields isolated disk-shaped clusters and then long linear structures. Our theory is coherent with experimental estimates, suggesting that a tilt-induced clustering mechanism is relevant in the context of cell adhesion proteins., Comment: 6 pages, 3 figures, with SI (ancillary files)
Published: 2023

40. Chromatin remodeling due to transient-link-and-pass activity enhances subnuclear dynamics

Author: Das, Rakesh, Sakaue, Takahiro, Shivashankar, G. V., Prost, Jacques, and Hiraiwa, Tetsuya
Subjects: Physics - Biological Physics, Condensed Matter - Soft Condensed Matter, Quantitative Biology - Subcellular Processes
Abstract: Spatiotemporal coordination of chromatin and subnuclear compartments is crucial for cells. Numerous enzymes act inside nucleus\textemdash some of those transiently link and pass two chromatin segments. Here we study how such an active perturbation affects fluctuating dynamics of an inclusion in the chromatic medium. Using numerical simulations and a versatile effective model, we categorize inclusion dynamics into three distinct modes. The transient-link-and-pass activity speeds up inclusion dynamics by affecting a slow mode related to chromatin remodeling, viz., size and shape of the chromatin meshes.
Published: 2023

41. Inverse problem regularization with hierarchical variational autoencoders

Author: Prost, Jean, Houdard, Antoine, Almansa, Andrés, and Papadakis, Nicolas
Subjects: Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning
Abstract: In this paper, we propose to regularize ill-posed inverse problems using a deep hierarchical variational autoencoder (HVAE) as an image prior. The proposed method synthesizes the advantages of i) denoiser-based Plug \& Play approaches and ii) generative model based approaches to inverse problems. First, we exploit VAE properties to design an efficient algorithm that benefits from convergence guarantees of Plug-and-Play (PnP) methods. Second, our approach is not restricted to specialized datasets and the proposed PnP-HVAE model is able to solve image restoration problems on natural images of any size. Our experiments show that the proposed PnP-HVAE method is competitive with both SOTA denoiser-based PnP approaches, and other SOTA restoration methods based on generative models.
Published: 2023
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42. Evolution of chemosensory and detoxification gene families across herbivorous Drosophilidae

Author: Peláez, Julianne N, Gloss, Andrew D, Goldman-Huertas, Benjamin, Kim, Bernard, Lapoint, Richard T, Pimentel-Solorio, Giovani, Verster, Kirsten I, Aguilar, Jessica M, Nelson Dittrich, Anna C, Singhal, Malvika, Suzuki, Hiromu C, Matsunaga, Teruyuki, Armstrong, Ellie E, Charboneau, Joseph LM, Groen, Simon C, Hembry, David H, Ochoa, Christopher J, O'Connor, Timothy K, Prost, Stefan, Zaaijer, Sophie, Nabity, Paul D, Wang, Jiarui, Rodas, Esteban, Liang, Irene, and Whiteman, Noah K
Subjects: Nutrition, Genetics, Animals, Herbivory, Drosophila, Insecta, Drosophila Proteins, Genomics, Phylogeny, Evolution, Molecular, Drosophila, Scaptomyza, adaptation, gene family evolution, genomics, plant-herbivore interactions, trophic shift
Abstract: Herbivorous insects are exceptionally diverse, accounting for a quarter of all known eukaryotic species, but the genomic basis of adaptations that enabled this dietary transition remains poorly understood. Many studies have suggested that expansions and contractions of chemosensory and detoxification gene families-genes directly mediating interactions with plant chemical defenses-underlie successful plant colonization. However, this hypothesis has been challenging to test because the origins of herbivory in many insect lineages are ancient (>150 million years ago (mya)), obscuring genomic evolutionary patterns. Here, we characterized chemosensory and detoxification gene family evolution across Scaptomyza, a genus nested within Drosophila that includes a recently derived (
Published: 2023

43. S2k guidelines on the management of paraneoplastic pemphigus/paraneoplastic autoimmune multiorgan syndrome initiated by the European Academy of Dermatology and Venereology (EADV)

Author: Antiga, Emiliano, Bech, Rikke, Maglie, Roberto, Genovese, Giovanni, Borradori, Luca, Bockle, Barbara, Caproni, Marzia, Caux, Frédéric, Chandran, Nisha Suyien, Corrà, Alberto, D'Amore, Francesco, Daneshpazhooh, Maryam, De, Dipankar, Didona, Dario, Dmochowski, Marian, Drenovska, Kossara, Ehrchen, Jan, Feliciani, Claudio, Goebeler, Matthias, Groves, Richard, Günther, Claudia, Handa, Sanjeev, Hofmann, Silke C, Horvath, Barbara, Ioannidis, Dimitrios, Jedlickova, Hana, Kowalewski, Cezary, Kridin, Khalaf, Joly, Pascal, Lim, Yen Loo, Marinovic, Branka, Maverakis, Emanual, Meijer, Joost, Patsatsi, Aikaterini, Pincelli, Carlo, Prost, Catherine, Setterfield, Jane, Sprecher, Eli, Skiljevic, Dusan, Tasanen, Kaisa, Uzun, Soner, Van Beek, Nina, Vassileva, Snejina, Vorobyev, Artem, Vujic, Igor, Wang, Gang, Wang, Mingyue, Wozniak, Katarzyna, Yayli, Savas, Zambruno, Giovanna, Hashimoto, Takashi, Schmidt, Enno, Mascarò, José Manuel, and Marzano, Angelo Valerio
Subjects: Biomedical and Clinical Sciences, Clinical Sciences, Rare Diseases, Autoimmune Disease, Animals, Rats, Autoimmune Diseases, Neoplasms, Paraneoplastic Syndromes, Paraneoplastic Syndromes, Nervous System, Societies, Medical, Dermatology & Venereal Diseases, Clinical sciences
Abstract: BackgroundParaneoplastic pemphigus (PNP), also called paraneoplastic autoimmune multiorgan syndrome (PAMS), is a rare autoimmune disease with mucocutaneous and multi-organ involvement. PNP/PAMS is typically associated with lymphoproliferative or haematological malignancies, and less frequently with solid malignancies. The mortality rate of PNP/PAMS is elevated owing to the increased risk of severe infections and disease-associated complications, such as bronchiolitis obliterans.ObjectivesThese guidelines summarize evidence-based and expert-based recommendations (S2k level) for the clinical characterization, diagnosis and management of PNP/PAMS. They have been initiated by the Task Force Autoimmune Blistering Diseases of the European Academy of Dermatology and Venereology with the contribution of physicians from all relevant disciplines. The degree of consent among all task force members was included.ResultsChronic severe mucositis and polymorphic skin lesions are clue clinical characteristics of PNP/PAMS. A complete assessment of the patient with suspected PNP/PAMS, requiring histopathological study and immunopathological investigations, including direct and indirect immunofluorescence, ELISA and, where available, immunoblotting/immunoprecipitation, is recommended to achieve a diagnosis of PNP/PAMS. Detection of anti-envoplakin antibodies and/or circulating antibodies binding to the rat bladder epithelium at indirect immunofluorescence is the most specific tool for the diagnosis of PNP/PAMS in a patient with compatible clinical and anamnestic features. Treatment of PNP/PAMS is highly challenging. Systemic steroids up to 1.5 mg/kg/day are recommended as first-line option. Rituximab is also recommended in patients with PNP/PAMS secondary to lymphoproliferative conditions but might also be considered in cases of PNP/PAMS associated with solid tumours. A multidisciplinary approach involving pneumologists, ophthalmologists and onco-haematologists is recommended for optimal management of the patients.ConclusionsThese are the first European guidelines for the diagnosis and management of PNP/PAMS. Diagnostic criteria and therapeutic recommendations will require further validation by prospective studies.
Published: 2023

44. Impact of Ovarian Cancer Surgery Volume on Overall and Progression-Free Survival: A Population-Based Retrospective National French Study

Author: Prost, Pauline, Duraes, Martha, Georgescu, Vera, Rebel, Lucie, Mercier, Grégoire, and Rathat, Gauthier
Published: 2024
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45. Renal replacement therapy initiation strategies in comatose patients with severe acute kidney injury: a secondary analysis of a multicenter randomized controlled trial

Author: Rambaud, Thomas, Hajage, David, Dreyfuss, Didier, Lebbah, Saïd, Martin-Lefevre, Laurent, Louis, Guillaume, Moschietto, Sébastien, Titeca-Beauport, Dimitri, La Combe, Béatrice, Pons, Bertrand, De Prost, Nicolas, Besset, Sébastien, Combes, Alain, Robine, Adrien, Beuzelin, Marion, Badie, Julio, Chevrel, Guillaume, Bohe, Julien, Coupez, Elisabeth, Chudeau, Nicolas, Barbar, Saber, Vinsonneau, Christophe, Forel, Jean-Marie, Thevenin, Didier, Boulet, Eric, Lakhal, Karim, Aissaoui, Nadia, Grange, Steven, Leone, Marc, Lacave, Guillaume, Nseir, Saad, Poirson, Florent, Mayaux, Julien, Ashenoune, Karim, Geri, Guillaume, Klouche, Kada, Thiery, Guillaume, Argaud, Laurent, Rozec, Bertrand, Cadoz, Cyril, Andreu, Pascal, Reignier, Jean, Ricard, Jean-Damien, Quenot, Jean-Pierre, Sonneville, Romain, and Gaudry, Stéphane
Published: 2024
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46. Inheritance and Blockchain: Thoughts and Open Questions

Author: Prost, Frédéric
Subjects: Computer Science - Cryptography and Security, K.4.2, K.5.m
Abstract: Inheritance is the fundamental building block of civilization. This is the addition of wealth, knowledge and properties over time that produce the society in which we are living. Every generation does not have to start from zero and can capitalize on the efforts of previous generations. Blockchain based assets are very efficiently and securely transferred between living entities. Yet the actual way to make heirs inherit crypto-assets is seldom discussed. It appears that the problems linked with the inheritance of crypto-assets raise a lot of technical, societal and legal issues. Part of those issues have to be tackled with at the level of the blockchain infrastructure itself. The aim of this paper is to open a research field, and to discuss some ideas, with regards to this overlooked issue. Inheritance is neither a peripheral question nor one that can be dodged. It comes with its own set of challenges that have to be met if blockchain based finance, and asset management, is to be taken seriously., Comment: arXiv admin note: text overlap with arXiv:2209.11194
Published: 2022

47. Electrohydraulic activity of biological cells

Author: Popović, Marko, Prost, Jacques, and Jülicher, Frank
Subjects: Physics - Biological Physics
Abstract: Fluid pumping and the generation of electric current by living tissues are required during morphogenetic processes and for maintainance of homeostasis. How these flows emerge from active and passive ion transport in cells has been well established. However, the interplay between flow and current generation is not well understood. Here, we study the electro-hydraulic coupling that arises from cell ion pumping. We develop a one-dimensional continuum model of fluid and ion transport across active cell membranes. Solving the Nernst-Planck and Poisson equations in the limit of weak charge imbalance allows us to derive approximate analytical solutions of the model. These approximations, consistent with the numerical results in physiologically relevant regime of parameters, allow us to describe electro-hydraulic activity of cells and tissues in terms of experimentally accessible parameters.
Published: 2022

48. SCOTCH and SODA: A Transformer Video Shadow Detection Framework

Author: Liu, Lihao, Prost, Jean, Zhu, Lei, Papadakis, Nicolas, Liò, Pietro, Schönlieb, Carola-Bibiane, and Aviles-Rivero, Angelica I
Subjects: Computer Science - Computer Vision and Pattern Recognition
Abstract: Shadows in videos are difficult to detect because of the large shadow deformation between frames. In this work, we argue that accounting for shadow deformation is essential when designing a video shadow detection method. To this end, we introduce the shadow deformation attention trajectory (SODA), a new type of video self-attention module, specially designed to handle the large shadow deformations in videos. Moreover, we present a new shadow contrastive learning mechanism (SCOTCH) which aims at guiding the network to learn a unified shadow representation from massive positive shadow pairs across different videos. We demonstrate empirically the effectiveness of our two contributions in an ablation study. Furthermore, we show that SCOTCH and SODA significantly outperforms existing techniques for video shadow detection. Code is available at the project page: https://lihaoliu-cambridge.github.io/scotch_and_soda/, Comment: Accepted to CVPR 2023
Published: 2022

49. Simpson's Paradox in Recommender Fairness: Reconciling differences between per-user and aggregated evaluations

Author: Prost, Flavien, Packer, Ben, Chen, Jilin, Wei, Li, Kremp, Pierre, Blumm, Nicholas, Wang, Susan, Doshi, Tulsee, Osadebe, Tonia, Heldt, Lukasz, Chi, Ed H., and Beutel, Alex
Subjects: Computer Science - Information Retrieval, Computer Science - Artificial Intelligence, Computer Science - Machine Learning
Abstract: There has been a flurry of research in recent years on notions of fairness in ranking and recommender systems, particularly on how to evaluate if a recommender allocates exposure equally across groups of relevant items (also known as provider fairness). While this research has laid an important foundation, it gave rise to different approaches depending on whether relevant items are compared per-user/per-query or aggregated across users. Despite both being established and intuitive, we discover that these two notions can lead to opposite conclusions, a form of Simpson's Paradox. We reconcile these notions and show that the tension is due to differences in distributions of users where items are relevant, and break down the important factors of the user's recommendations. Based on this new understanding, practitioners might be interested in either notions, but might face challenges with the per-user metric due to partial observability of the relevance and user satisfaction, typical in real-world recommenders. We describe a technique based on distribution matching to estimate it in such a scenario. We demonstrate on simulated and real-world recommender data the effectiveness and usefulness of such an approach.
Published: 2022

50. Neural networks for first order HJB equations and application to front propagation with obstacle terms

Author: Bokanowski, Olivier, Warin, Xavier, and Prost, Averil
Subjects: Mathematics - Optimization and Control, 35F21, 49L20, 68T07
Abstract: We consider a deterministic optimal control problem with a maximum running cost functional, in a finite horizon context, and propose deep neural network approximations for Bellman's dynamic programming principle, corresponding also to some first-order Hamilton-Jacobi-Bellman equations. This work follows the lines of Hur\'e et al. (SIAM J. Numer. Anal., vol. 59 (1), 2021, pp. 525-557) where algorithms are proposed in a stochastic context. However, we need to develop a completely new approach in order to deal with the propagation of errors in the deterministic setting, where no diffusion is present in the dynamics. Our analysis gives precise error estimates in an average norm. The study is then illustrated on several academic numerical examples related to front propagations models in the presence of obstacle constraints, showing the relevance of the approach for average dimensions (e.g. from $2$ to $8$), even for non-smooth value functions.
Published: 2022

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