46 results on '"Qianxiao Li"'
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2. Mitigating distribution shift in machine learning-augmented hybrid simulation.
3. From Generalization Analysis to Optimization Designs for State Space Models.
4. DynGMA: a robust approach for learning stochastic differential equations from data.
5. Accelerating Legacy Numerical Solvers by Non-intrusive Gradient-based Meta-solving.
6. PID Control-Based Self-Healing to Improve the Robustness of Large Language Models.
7. Forward and Inverse Approximation Theory for Linear Temporal Convolutional Networks.
8. Inverse Approximation Theory for Nonlinear Recurrent Neural Networks.
9. Constructing Custom Thermodynamics Using Deep Learning.
10. Asymptotically Fair Participation in Machine Learning Models: an Optimal Control Perspective.
11. Interpolation, Approximation and Controllability of Deep Neural Networks.
12. StableSSM: Alleviating the Curse of Memory in State-space Models through Stable Reparameterization.
13. A Brief Survey on the Approximation Theory for Sequence Modelling.
14. Approximation theory of transformer networks for sequence modeling.
15. Deep Neural Network Approximation of Invariant Functions through Dynamical Systems.
16. On the Universal Approximation Property of Deep Fully Convolutional Neural Networks.
17. A Recursively Recurrent Neural Network (R2N2) Architecture for Learning Iterative Algorithms.
18. Transfer Learning for Rapid Extraction of Thickness from Optical Spectra of Semiconductor Thin Films.
19. Self-Healing Robust Neural Networks via Closed-Loop Control.
20. Accelerating numerical methods by gradient-based meta-solving.
21. Fast Bayesian Optimization of Needle-in-a-Haystack Problems using Zooming Memory-Based Initialization.
22. Connecting Optimization and Generalization via Gradient Flow Path Length.
23. Approximation Theory of Convolutional Architectures for Time Series Modelling.
24. Computing the Invariant Distribution of Randomly Perturbed Dynamical Systems Using Deep Learning.
25. Towards Robust Neural Networks via Close-loop Control.
26. Personalized Algorithm Generation: A Case Study in Meta-Learning ODE Integrators.
27. QROSS: QUBO Relaxation Parameter Optimisation via Learning Solver Surrogates.
28. OnsagerNet: Learning Stable and Interpretable Dynamics using a Generalized Onsager Principle.
29. Inverse design of crystals using generalized invertible crystallographic representation.
30. Amata: An Annealing Mechanism for Adversarial Training Acceleration.
31. A Data Driven Method for Computing Quasipotentials.
32. Optimising Stochastic Routing for Taxi Fleets with Model Enhanced Reinforcement Learning.
33. Optimization in Machine Learning: A Distribution Space Approach.
34. On the Curse of Memory in Recurrent Neural Networks: Approximation and Optimization Analysis.
35. Collaborative Inference for Efficient Remote Monitoring.
36. Computing Committor Functions for the Study of Rare Events Using Deep Learning.
37. Deep Learning via Dynamical Systems: An Approximation Perspective.
38. Distributed Optimization for Over-Parameterized Learning.
39. Machine learning enables polymer cloud-point engineering via inverse design.
40. An Optimal Control Approach to Deep Learning and Applications to Discrete-Weight Neural Networks.
41. Stochastic Modified Equations and Dynamics of Stochastic Gradient Algorithms I: Mathematical Foundations.
42. A Mean-Field Optimal Control Formulation of Deep Learning.
43. Dynamics of Taxi-like Logistics Systems: Theory and Microscopic Simulations.
44. On the Convergence and Robustness of Batch Normalization.
45. Maximum Principle Based Algorithms for Deep Learning.
46. Dynamics of Stochastic Gradient Algorithms.
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