Conditional Deep Gaussian Processes: empirical Bayes hyperdata learning

Conditional Deep Gaussian Processes: empirical Bayes hyperdata learning

1 October 2021

Patrick Shafto

Papers citing "Conditional Deep Gaussian Processes: empirical Bayes hyperdata learning"

6 / 6 papers shown

Title
On Connecting Deep Trigonometric Networks with Deep Gaussian Processes: Covariance, Expressivity, and Neural Tangent Kernel Chi-Ken Lu Patrick Shafto BDL 34 0 0 14 Mar 2022
Characterizing Deep Gaussian Processes via Nonlinear Recurrence Systems Anh Tong Jaesik Choi 21 2 0 19 Oct 2020
Conditional Deep Gaussian Processes: multi-fidelity kernel learning Chi-Ken Lu Patrick Shafto 11 5 0 07 Feb 2020
Benefits of depth in neural networks Matus Telgarsky 142 602 0 14 Feb 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 285 9,138 0 06 Jun 2015
Manifold Gaussian Processes for Regression Roberto Calandra Jan Peters C. Rasmussen M. Deisenroth 86 271 0 24 Feb 2014