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791 results on '"Johnson, Timothy D"'

1. Playing Games: Joseph Hooker and the Politics of Command

Author

Parrish, T. Michael, Smith, Timothy B., Zander, Cecily N., Wills, Brian Steel, Symonds, Craig L., Murray, Jennifer M., Glatthaar, Joseph T., Engle, Stephen D., Cutrer, Thomas W., Rafuse, Ethan S., Mendoza, Alexander, Keller, Christian B., Chick, Sean, Gallagher, Gary W., and Johnson, Timothy D.

Published
2024

2. When a Little Slow Mattered Most: George H. Thomas in Mexico

Author

Parrish, T. Michael, Smith, Timothy B., Zander, Cecily N., Wills, Brian Steel, Symonds, Craig L., Murray, Jennifer M., Glatthaar, Joseph T., Engle, Stephen D., Cutrer, Thomas W., Rafuse, Ethan S., Mendoza, Alexander, Keller, Christian B., Chick, Sean, Gallagher, Gary W., and Johnson, Timothy D.

Published
2024

3. Half Title Page, Title Page, Copyright

Author

Parrish, T. Michael, Smith, Timothy B., Zander, Cecily N., Wills, Brian Steel, Symonds, Craig L., Murray, Jennifer M., Glatthaar, Joseph T., Engle, Stephen D., Cutrer, Thomas W., Rafuse, Ethan S., Mendoza, Alexander, Keller, Christian B., Chick, Sean, Gallagher, Gary W., and Johnson, Timothy D.

Published
2024

5. Index

Author

Parrish, T. Michael, Smith, Timothy B., Zander, Cecily N., Wills, Brian Steel, Symonds, Craig L., Murray, Jennifer M., Glatthaar, Joseph T., Engle, Stephen D., Cutrer, Thomas W., Rafuse, Ethan S., Mendoza, Alexander, Keller, Christian B., Chick, Sean, Gallagher, Gary W., and Johnson, Timothy D.

Published
2024

6. Foreword

Author

Parrish, T. Michael, Smith, Timothy B., Zander, Cecily N., Wills, Brian Steel, Symonds, Craig L., Murray, Jennifer M., Glatthaar, Joseph T., Engle, Stephen D., Cutrer, Thomas W., Rafuse, Ethan S., Mendoza, Alexander, Keller, Christian B., Chick, Sean, Gallagher, Gary W., and Johnson, Timothy D.

Published
2024

7. The Training of Lee's Future Lieutenant: Thomas J. Jackson's Mexican War

Author

Parrish, T. Michael, Smith, Timothy B., Zander, Cecily N., Wills, Brian Steel, Symonds, Craig L., Murray, Jennifer M., Glatthaar, Joseph T., Engle, Stephen D., Cutrer, Thomas W., Rafuse, Ethan S., Mendoza, Alexander, Keller, Christian B., Chick, Sean, Gallagher, Gary W., and Johnson, Timothy D.

Published
2024

8. Acknowledgments

Author

Parrish, T. Michael, Smith, Timothy B., Zander, Cecily N., Wills, Brian Steel, Symonds, Craig L., Murray, Jennifer M., Glatthaar, Joseph T., Engle, Stephen D., Cutrer, Thomas W., Rafuse, Ethan S., Mendoza, Alexander, Keller, Christian B., Chick, Sean, Gallagher, Gary W., and Johnson, Timothy D.

Published
2024

9. Maps

Author

Parrish, T. Michael, Smith, Timothy B., Zander, Cecily N., Wills, Brian Steel, Symonds, Craig L., Murray, Jennifer M., Glatthaar, Joseph T., Engle, Stephen D., Cutrer, Thomas W., Rafuse, Ethan S., Mendoza, Alexander, Keller, Christian B., Chick, Sean, Gallagher, Gary W., and Johnson, Timothy D.

Published
2024

10. Contributors

Author

Parrish, T. Michael, Smith, Timothy B., Zander, Cecily N., Wills, Brian Steel, Symonds, Craig L., Murray, Jennifer M., Glatthaar, Joseph T., Engle, Stephen D., Cutrer, Thomas W., Rafuse, Ethan S., Mendoza, Alexander, Keller, Christian B., Chick, Sean, Gallagher, Gary W., and Johnson, Timothy D.

Published
2024

11. The Quest for Recognition and Glory: P. G. T. Beauregard in Mexico

Author

Parrish, T. Michael, Smith, Timothy B., Zander, Cecily N., Wills, Brian Steel, Symonds, Craig L., Murray, Jennifer M., Glatthaar, Joseph T., Engle, Stephen D., Cutrer, Thomas W., Rafuse, Ethan S., Mendoza, Alexander, Keller, Christian B., Chick, Sean, Gallagher, Gary W., and Johnson, Timothy D.

Published
2024

15. Sour Grapes: Braxton Bragg and the Lessons of the War with Mexico

Author

Parrish, T. Michael, Smith, Timothy B., Zander, Cecily N., Wills, Brian Steel, Symonds, Craig L., Murray, Jennifer M., Glatthaar, Joseph T., Engle, Stephen D., Cutrer, Thomas W., Rafuse, Ethan S., Mendoza, Alexander, Keller, Christian B., Chick, Sean, Gallagher, Gary W., and Johnson, Timothy D.

Published
2024

17. Lofty Expectations: Don Carlos Buell's Mexican-American War Education

Author

Parrish, T. Michael, Smith, Timothy B., Zander, Cecily N., Wills, Brian Steel, Symonds, Craig L., Murray, Jennifer M., Glatthaar, Joseph T., Engle, Stephen D., Cutrer, Thomas W., Rafuse, Ethan S., Mendoza, Alexander, Keller, Christian B., Chick, Sean, Gallagher, Gary W., and Johnson, Timothy D.

Published
2024

19. Bibliography

Author

Johnson, Timothy D.

Published
2018

20. Back Cover

Author

Johnson, Timothy D.

Published
2018

24. Index

Author

Johnson, Timothy D.

Published
2018

25. Notes

Author

Johnson, Timothy D.

Published
2018

26. Appendixes

Author

Johnson, Timothy D.

Published
2018

28. Epilogue

Author

Johnson, Timothy D.

Published
2018

38. Prologue

Author

Johnson, Timothy D.

Published
2018

41. Cover

Author

Johnson, Timothy D.

Published
2018

43. Scalable Bayesian Image-on-Scalar Regression for Population-Scale Neuroimaging Data Analysis

Author

Xu, Yuliang, Johnson, Timothy D., Nichols, Thomas E., and Kang, Jian

Subjects
Statistics - Applications, Statistics - Computation
Abstract

Bayesian Image-on-Scalar Regression (ISR) offers significant advantages for neuroimaging data analysis, including flexibility and the ability to quantify uncertainty. However, its application to large-scale imaging datasets, such as found in the UK Biobank, is hindered by the computational demands of traditional posterior computation methods, as well as the challenge of individual-specific brain masks that deviate from the common mask typically used in standard ISR approaches. To address these challenges, we introduce a novel Bayesian ISR model that is scalable and accommodates inconsistent brain masks across subjects in large-scale imaging studies. Our model leverages Gaussian process priors and integrates salience area indicators to facilitate ISR. We develop a cutting-edge scalable posterior computation algorithm that employs stochastic gradient Langevin dynamics coupled with memory mapping techniques, ensuring that computation time scales linearly with subsample size and memory usage is constrained only by the batch size. Our approach uniquely enables direct spatial posterior inferences on brain activation regions. The efficacy of our method is demonstrated through simulations and analysis of the UK Biobank task fMRI data, encompassing 38,639 subjects and over 120,000 voxels per image, showing that it can achieve a speed increase of 4 to 11 times and enhance statistical power by 8% to 18% compared to traditional Gibbs sampling with zero-imputation in various simulation scenarios.

Published
2024

44. Scalable Scalar-on-Image Cortical Surface Regression with a Relaxed-Thresholded Gaussian Process Prior

Author

Menacher, Anna, Nichols, Thomas E., Johnson, Timothy D., and Kang, Jian

Subjects
Statistics - Methodology, Statistics - Applications
Abstract

In addressing the challenge of analysing the large-scale Adolescent Brain Cognition Development (ABCD) fMRI dataset, involving over 5,000 subjects and extensive neuroimaging data, we propose a scalable Bayesian scalar-on-image regression model for computational feasibility and efficiency. Our model employs a relaxed-thresholded Gaussian process (RTGP), integrating piecewise-smooth, sparse, and continuous functions capable of both hard- and soft-thresholding. This approach introduces additional flexibility in feature selection in scalar-on-image regression and leads to scalable posterior computation by adopting a variational approximation and utilising the Karhunen-Lo\`eve expansion for Gaussian processes. This advancement substantially reduces the computational costs in vertex-wise analysis of cortical surface data in large-scale Bayesian spatial models. The model's parameter estimation and prediction accuracy and feature selection performance are validated through extensive simulation studies and an application to the ABCD study. Here, we perform regression analysis correlating intelligence scores with task-based functional MRI data, taking into account confounding factors including age, sex, and parental education level. This validation highlights our model's capability to handle large-scale neuroimaging data while maintaining computational feasibility and accuracy., Comment: For supplementary materials, see https://drive.google.com/file/d/1SNS0T6ptIGLfs67zYrZ9Bz0-DgzCIRgz/view?usp=sharing . For code, see https://github.com/annamenacher/RTGP

Published
2024

46. Acknowledgments

Author

Hughes, Nathaniel Cheairs Jr., Stonesifer, Roy P., and Johnson, Timothy D.

Published
2011

47. Cover

Author

Hughes, Nathaniel Cheairs Jr., Stonesifer, Roy P., and Johnson, Timothy D.

Published
2011

49. 2. A Friend Indeed

Author

Hughes, Nathaniel Cheairs Jr., Stonesifer, Roy P., and Johnson, Timothy D.

Published
2011

50. 1. A Jacksonian Tradition

Author

Hughes, Nathaniel Cheairs Jr., Stonesifer, Roy P., and Johnson, Timothy D.

Published
2011

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