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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

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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

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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

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Bias-Free Scalable Gaussian Processes via Randomized Truncations

Feb 12, 2021
Andres Potapczynski, Luhuan Wu, Dan Biderman, Geoff Pleiss, John P. Cunningham

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Uses and Abuses of the Cross-Entropy Loss: Case Studies in Modern Deep Learning

Nov 10, 2020
Elliott Gordon-Rodriguez, Gabriel Loaiza-Ganem, Geoff Pleiss, John P. Cunningham

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General linear-time inference for Gaussian Processes on one dimension

Mar 11, 2020
Jackson Loper, David Blei, John P. Cunningham, Liam Paninski

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The continuous categorical: a novel simplex-valued exponential family

Feb 20, 2020
Elliott Gordon-Rodriguez, Gabriel Loaiza-Ganem, John P. Cunningham

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