Deep Gaussian Processes

2 November 2012

Papers citing "Deep Gaussian Processes"

26 / 26 papers shown

Title
Efficient Transformed Gaussian Process State-Space Models for Non-Stationary High-Dimensional Dynamical Systems Zhidi Lin Ying Li Feng Yin Juan Maroñas Alexandre Thiéry 93 0 0 24 Mar 2025
Uncertainty Quantification With Noise Injection in Neural Networks: A Bayesian Perspective Xueqiong Yuan Jipeng Li E. Kuruoglu UQCV BDL 61 0 0 21 Jan 2025
Bayesian Adaptive Calibration and Optimal Design Rafael Oliveira Dino Sejdinovic David Howard Edwin Bonilla 126 0 0 20 Jan 2025
Stochastic Process Learning via Operator Flow Matching Yaozhong Shi Zachary E. Ross D. Asimaki Kamyar Azizzadenesheli 91 2 0 10 Jan 2025
Compactly-supported nonstationary kernels for computing exact Gaussian processes on big data M. Risser M. Noack Hengrui Luo Ronald Pandolfi GP 51 0 0 07 Nov 2024
Residual Deep Gaussian Processes on Manifolds Kacper Wyrwal Andreas Krause Viacheslav Borovitskiy BDL 70 0 0 31 Oct 2024
Federated Neural Nonparametric Point Processes Hui Chen Hengyu Liu Hengyu Liu Xuhui Fan Zhilin Zhao Feng Zhou Christopher J. Quinn Longbing Cao FedML 59 0 0 08 Oct 2024
Deep Kernel Posterior Learning under Infinite Variance Prior Weights Jorge Loría A. Bhadra BDL UQCV 83 0 0 02 Oct 2024
Adaptive RKHS Fourier Features for Compositional Gaussian Process Models Xinxing Shi Thomas Baldwin-McDonald Mauricio A. Álvarez 91 0 0 01 Jul 2024
Posterior and variational inference for deep neural networks with heavy-tailed weights Ismael Castillo Paul Egels BDL 71 4 0 05 Jun 2024
Deep Horseshoe Gaussian Processes Ismael Castillo Thibault Randrianarisoa BDL UQCV 60 5 0 04 Mar 2024
On Neural Networks as Infinite Tree-Structured Probabilistic Graphical Models Yue Liu Alexandar J. Thomson Matthew M. Engelhard David Page David Page BDL AI4CE 41 0 0 27 May 2023
Relaxed Gaussian process interpolation: a goal-oriented approach to Bayesian optimization S. Petit Julien Bect E. Vázquez 73 1 0 07 Jun 2022
Machine Learning for Reliability Engineering and Safety Applications: Review of Current Status and Future Opportunities Zhaoyi Xu J. Saleh 46 342 0 19 Aug 2020
Machine Learning for Robust Identification of Complex Nonlinear Dynamical Systems: Applications to Earth Systems Modeling Nishant Yadav S. Ravela A. Ganguly OOD AI4Cl AI4CE 29 3 0 12 Aug 2020
Tensor Programs I: Wide Feedforward or Recurrent Neural Networks of Any Architecture are Gaussian Processes Greg Yang 61 197 0 28 Oct 2019
A trans-disciplinary review of deep learning research for water resources scientists Chaopeng Shen AI4CE 110 685 0 06 Dec 2017
Avoiding pathologies in very deep networks David Duvenaud Oren Rippel Ryan P. Adams Zoubin Ghahramani ODL BDL 74 158 0 24 Feb 2014
Distributed Variational Inference in Sparse Gaussian Process Regression and Latent Variable Models Y. Gal Mark van der Wilk C. Rasmussen 47 150 0 06 Feb 2014
Gaussian Processes for Big Data J. Hensman Nicolò Fusi Neil D. Lawrence GP 70 1,226 0 26 Sep 2013
Stochastic Variational Inference Matt Hoffman David M. Blei Chong-Jun Wang John Paisley BDL 174 2,605 0 29 Jun 2012
Manifold Relevance Determination Andreas C. Damianou Carl Henrik Ek Michalis K. Titsias Neil D. Lawrence 49 109 0 18 Jun 2012
Gaussian Process Regression Networks A. Wilson David A. Knowles Zoubin Ghahramani GP BDL 114 192 0 19 Oct 2011
Variational Gaussian Process Dynamical Systems Andreas C. Damianou Michalis K. Titsias Neil D. Lawrence DRL 62 105 0 25 Jul 2011
Additive Kernels for Gaussian Process Modeling N. Durrande D. Ginsbourger O. Roustant 52 25 0 21 Mar 2011
On Nonparametric Guidance for Learning Autoencoder Representations Jasper Snoek Ryan P. Adams Hugo Larochelle DRL SSL 290 20 0 08 Feb 2011