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Pathwise Conditioning of Gaussian Processes

8 November 2020

James T. Wilson

Viacheslav Borovitskiy

Papers citing "Pathwise Conditioning of Gaussian Processes"

45 / 45 papers shown

Title
Residual Deep Gaussian Processes on Manifolds Kacper Wyrwal Andreas Krause Viacheslav Borovitskiy BDL 85 0 0 31 Oct 2024
Optimizing Posterior Samples for Bayesian Optimization via Rootfinding Taiwo A. Adebiyi Bach Do Ruda Zhang 186 2 0 29 Oct 2024
Linearization Turns Neural Operators into Function-Valued Gaussian Processes Emilia Magnani Marvin Pfortner Tobias Weber Philipp Hennig UQCV 105 1 0 07 Jun 2024
Improving Linear System Solvers for Hyperparameter Optimisation in Iterative Gaussian Processes J. Lin Shreyas Padhy Bruno Mlodozeniec Javier Antorán José Miguel Hernández-Lobato 69 3 0 28 May 2024
Matérn Gaussian Processes on Graphs Viacheslav Borovitskiy I. Azangulov Alexander Terenin P. Mostowsky M. Deisenroth N. Durrande 42 82 0 29 Oct 2020
Convergence of Sparse Variational Inference in Gaussian Processes Regression David R. Burt C. Rasmussen Mark van der Wilk 75 74 0 01 Aug 2020
Fast Matrix Square Roots with Applications to Gaussian Processes and Bayesian Optimization Geoff Pleiss M. Jankowiak David Eriksson Anil Damle Jacob R. Gardner 63 43 0 19 Jun 2020
Matérn Gaussian processes on Riemannian manifolds Viacheslav Borovitskiy Alexander Terenin P. Mostowsky M. Deisenroth 85 123 0 17 Jun 2020
Linear-time inference for Gaussian Processes on one dimension Jackson Loper David M. Blei John P. Cunningham Liam Paninski 33 17 0 11 Mar 2020
A Framework for Interdomain and Multioutput Gaussian Processes Mark van der Wilk Vincent Dutordoir S. T. John A. Artemev Vincent Adam J. Hensman 68 95 0 02 Mar 2020
Efficiently Sampling Functions from Gaussian Process Posteriors James T. Wilson Viacheslav Borovitskiy Alexander Terenin P. Mostowsky M. Deisenroth 56 165 0 21 Feb 2020
Overcoming Mean-Field Approximations in Recurrent Gaussian Process Models Alessandro Davide Ialongo Mark van der Wilk J. Hensman C. Rasmussen 72 30 0 13 Jun 2019
Know Your Boundaries: Constraining Gaussian Processes by Variational Harmonic Features Arno Solin Manon Kok 42 23 0 10 Apr 2019
Exact Gaussian Processes on a Million Data Points Ke Alexander Wang Geoff Pleiss Jacob R. Gardner Stephen Tyree Kilian Q. Weinberger A. Wilson GP 55 230 0 19 Mar 2019
Gaussian Process Optimization with Adaptive Sketching: Scalable and No Regret Daniele Calandriello Luigi Carratino A. Lazaric Michal Valko Lorenzo Rosasco GP 41 0 0 13 Mar 2019
Banded Matrix Operators for Gaussian Markov Models in the Automatic Differentiation Era N. Durrande Vincent Adam L. Bordeaux Stefanos Eleftheriadis J. Hensman 41 26 0 26 Feb 2019
Bayesian Image Classification with Deep Convolutional Gaussian Processes Vincent Dutordoir Mark van der Wilk A. Artemev J. Hensman UQCV BDL 142 32 0 15 Feb 2019
Deep learning with differential Gaussian process flows Pashupati Hegde Markus Heinonen Harri Lähdesmäki Samuel Kaski BDL 63 42 0 09 Oct 2018
Deep convolutional Gaussian processes Kenneth Blomqvist Samuel Kaski Markus Heinonen BDL 67 61 0 06 Oct 2018
GPyTorch: Blackbox Matrix-Matrix Gaussian Process Inference with GPU Acceleration Jacob R. Gardner Geoff Pleiss D. Bindel Kilian Q. Weinberger A. Wilson GP 136 1,100 0 28 Sep 2018
Orthogonally Decoupled Variational Gaussian Processes Hugh Salimbeni Ching-An Cheng Byron Boots M. Deisenroth 45 43 0 24 Sep 2018
A Tutorial on Bayesian Optimization P. Frazier GP 109 1,788 0 08 Jul 2018
Gaussian Processes and Kernel Methods: A Review on Connections and Equivalences Motonobu Kanagawa Philipp Hennig Dino Sejdinovic Bharath K. Sriperumbudur GP BDL 138 343 0 06 Jul 2018
Maximizing acquisition functions for Bayesian optimization James T. Wilson Frank Hutter M. Deisenroth 122 247 0 25 May 2018
Constant-Time Predictive Distributions for Gaussian Processes Geoff Pleiss Jacob R. Gardner Kilian Q. Weinberger A. Wilson 51 96 0 16 Mar 2018
Variational Inference for Gaussian Process Models with Linear Complexity Ching-An Cheng Byron Boots BDL 49 75 0 28 Nov 2017
Convolutional Gaussian Processes Mark van der Wilk C. Rasmussen J. Hensman BDL 71 132 0 06 Sep 2017
Data-Efficient Reinforcement Learning with Probabilistic Model Predictive Control Sanket Kamthe M. Deisenroth 128 217 0 20 Jun 2017
Parallel and Distributed Thompson Sampling for Large-scale Accelerated Exploration of Chemical Space José Miguel Hernández-Lobato James Requeima Edward O. Pyzer-Knapp Alán Aspuru-Guzik 76 185 0 06 Jun 2017
Batched Large-scale Bayesian Optimization in High-dimensional Spaces Zi Wang Clement Gehring Pushmeet Kohli Stefanie Jegelka UQCV 54 214 0 05 Jun 2017
Doubly Stochastic Variational Inference for Deep Gaussian Processes Hugh Salimbeni M. Deisenroth BDL GP 86 421 0 24 May 2017
Variational Fourier features for Gaussian processes J. Hensman N. Durrande Arno Solin VLM 68 200 0 21 Nov 2016
GPflow: A Gaussian process library using TensorFlow A. G. Matthews Mark van der Wilk T. Nickson Keisuke Fujii A. Boukouvalas Pablo León-Villagrá Zoubin Ghahramani J. Hensman GP 78 666 0 27 Oct 2016
On the Error of Random Fourier Features Danica J. Sutherland J. Schneider 78 192 0 09 Jun 2015
Kernel Interpolation for Scalable Structured Gaussian Processes (KISS-GP) A. Wilson H. Nickisch GP 69 513 0 03 Mar 2015
Gaussian Processes for Data-Efficient Learning in Robotics and Control M. Deisenroth Dieter Fox C. Rasmussen 120 694 0 10 Feb 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 1.9K 150,115 0 22 Dec 2014
Scalable Variational Gaussian Process Classification J. Hensman A. G. Matthews Zoubin Ghahramani BDL 75 644 0 07 Nov 2014
Hilbert Space Methods for Reduced-Rank Gaussian Process Regression Arno Solin Simo Särkkä 206 217 0 21 Jan 2014
Gaussian Processes for Big Data J. Hensman Nicolò Fusi Neil D. Lawrence GP 107 1,232 0 26 Sep 2013
Sinkhorn Distances: Lightspeed Computation of Optimal Transportation Distances Marco Cuturi OT 215 4,277 0 04 Jun 2013
Deep Gaussian Processes Andreas C. Damianou Neil D. Lawrence GP BDL 136 1,182 0 02 Nov 2012
Practical Bayesian Optimization of Machine Learning Algorithms Jasper Snoek Hugo Larochelle Ryan P. Adams 359 7,942 0 13 Jun 2012
Sequential design of computer experiments for the estimation of a probability of failure Julien Bect D. Ginsbourger Ling Li Victor Picheny E. Vázquez 97 349 0 27 Sep 2010
Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design Niranjan Srinivas Andreas Krause Sham Kakade Matthias Seeger 149 1,622 0 21 Dec 2009