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Posterior and Computational Uncertainty in Gaussian Processes


May 30, 2022
Jonathan Wenger, Geoff Pleiss, Marvin Pförtner, Philipp Hennig, John P. Cunningham


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Data Augmentation for Compositional Data: Advancing Predictive Models of the Microbiome


May 20, 2022
Elliott Gordon-Rodriguez, Thomas P. Quinn, John P. Cunningham


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On the Normalizing Constant of the Continuous Categorical Distribution


Apr 28, 2022
Elliott Gordon-Rodriguez, Gabriel Loaiza-Ganem, Andres Potapczynski, John P. Cunningham


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Deep Ensembles Work, But Are They Necessary?


Feb 14, 2022
Taiga Abe, E. Kelly Buchanan, Geoff Pleiss, Richard Zemel, John P. Cunningham


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Reducing the Variance of Gaussian Process Hyperparameter Optimization with Preconditioning


Jul 01, 2021
Jonathan Wenger, Geoff Pleiss, Philipp Hennig, John P. Cunningham, Jacob R. Gardner


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The Limitations of Large Width in Neural Networks: A Deep Gaussian Process Perspective


Jun 11, 2021
Geoff Pleiss, John P. Cunningham


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Rectangular Flows for Manifold Learning


Jun 02, 2021
Anthony L. Caterini, Gabriel Loaiza-Ganem, Geoff Pleiss, John P. Cunningham


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Simulating time to event prediction with spatiotemporal echocardiography deep learning


Mar 03, 2021
Rohan Shad, Nicolas Quach, Robyn Fong, Patpilai Kasinpila, Cayley Bowles, Kate M. Callon, Michelle C. Li, Jeffrey Teuteberg, John P. Cunningham, Curtis P. Langlotz, William Hiesinger

* 9 pages, 5 figures 

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Medical Imaging and Machine Learning


Mar 02, 2021
Rohan Shad, John P. Cunningham, Euan A. Ashley, Curtis P. Langlotz, William Hiesinger

* 9 pages, 4 figures 

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Predicting post-operative right ventricular failure using video-based deep learning


Feb 28, 2021
Rohan Shad, Nicolas Quach, Robyn Fong, Patpilai Kasinpila, Cayley Bowles, Miguel Castro, Ashrith Guha, Eddie Suarez, Stefan Jovinge, Sangjin Lee, Theodore Boeve, Myriam Amsallem, Xiu Tang, Francois Haddad, Yasuhiro Shudo, Y. Joseph Woo, Jeffrey Teuteberg, John P. Cunningham, Curt P. Langlotz, William Hiesinger

* 12 pages, 3 figures 

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