Efficiently Sampling Functions from Gaussian Process Posteriors

21 February 2020

James T. Wilson

Viacheslav Borovitskiy

Papers citing "Efficiently Sampling Functions from Gaussian Process Posteriors"

23 / 23 papers shown

Title
Computation-Aware Kalman Filtering and Smoothing Marvin Pfortner Jonathan Wenger Jon Cockayne Philipp Hennig 91 4 0 13 Mar 2025
Residual Deep Gaussian Processes on Manifolds Kacper Wyrwal Andreas Krause Viacheslav Borovitskiy BDL 68 0 0 31 Oct 2024
Optimizing Posterior Samples for Bayesian Optimization via Rootfinding Taiwo A. Adebiyi Bach Do Ruda Zhang 143 2 0 29 Oct 2024
Improving Linear System Solvers for Hyperparameter Optimisation in Iterative Gaussian Processes J. Lin Shreyas Padhy Bruno Mlodozeniec Javier Antorán José Miguel Hernández-Lobato 55 2 0 28 May 2024
Exact Gaussian Processes on a Million Data Points Ke Alexander Wang Geoff Pleiss Jacob R. Gardner Stephen Tyree Kilian Q. Weinberger A. Wilson GP 33 227 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 20 68 0 13 Mar 2019
Rates of Convergence for Sparse Variational Gaussian Process Regression David R. Burt C. Rasmussen Mark van der Wilk 45 152 0 08 Mar 2019
Orthogonally Decoupled Variational Gaussian Processes Hugh Salimbeni Ching-An Cheng Byron Boots M. Deisenroth 23 43 0 24 Sep 2018
Maximizing acquisition functions for Bayesian optimization James T. Wilson Frank Hutter M. Deisenroth 115 245 0 25 May 2018
Constant-Time Predictive Distributions for Gaussian Processes Geoff Pleiss Jacob R. Gardner Kilian Q. Weinberger A. Wilson 32 94 0 16 Mar 2018
Computational Optimal Transport Gabriel Peyré Marco Cuturi OT 115 2,133 0 01 Mar 2018
Variational Inference for Gaussian Process Models with Linear Complexity Ching-An Cheng Byron Boots BDL 31 75 0 28 Nov 2017
Data-Efficient Reinforcement Learning with Probabilistic Model Predictive Control Sanket Kamthe M. Deisenroth 97 217 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 37 181 0 06 Jun 2017
Batched Large-scale Bayesian Optimization in High-dimensional Spaces Zi Wang Clement Gehring Pushmeet Kohli Stefanie Jegelka UQCV 28 211 0 05 Jun 2017
Variational Fourier features for Gaussian processes J. Hensman N. Durrande Arno Solin VLM 39 200 0 21 Nov 2016
On the Error of Random Fourier Features Danica J. Sutherland J. Schneider 54 189 0 09 Jun 2015
Kernel Interpolation for Scalable Structured Gaussian Processes (KISS-GP) A. Wilson H. Nickisch GP 54 512 0 03 Mar 2015
Gaussian Processes for Data-Efficient Learning in Robotics and Control M. Deisenroth Dieter Fox C. Rasmussen 72 688 0 10 Feb 2015
Predictive Entropy Search for Efficient Global Optimization of Black-box Functions José Miguel Hernández-Lobato Matthew W. Hoffman Zoubin Ghahramani 57 646 0 10 Jun 2014
Gaussian Processes for Big Data J. Hensman Nicolò Fusi Neil D. Lawrence GP 57 1,226 0 26 Sep 2013
Sinkhorn Distances: Lightspeed Computation of Optimal Transportation Distances Marco Cuturi OT 97 4,210 0 04 Jun 2013
Practical Bayesian Optimization of Machine Learning Algorithms Jasper Snoek Hugo Larochelle Ryan P. Adams 249 7,883 0 13 Jun 2012