A Tutorial on Sparse Gaussian Processes and Variational Inference

A Tutorial on Sparse Gaussian Processes and Variational Inference

27 December 2020

Felix Leibfried

Vincent Dutordoir

Papers citing "A Tutorial on Sparse Gaussian Processes and Variational Inference"

9 / 9 papers shown

Title
A flexible Bayesian non-parametric mixture model reveals multiple dependencies of swap errors in visual working memory Puria Radmard Paul M. Bays Máté Lengyel 20 0 0 02 May 2025
Gradient-based Sample Selection for Faster Bayesian Optimization Qiyu Wei Haowei Wang Zirui Cao Songhao Wang Richard Allmendinger Mauricio A Álvarez 24 0 0 10 Apr 2025
Data-Efficient Kernel Methods for Learning Differential Equations and Their Solution Operators: Algorithms and Error Analysis Yasamin Jalalian Juan Felipe Osorio Ramirez Alexander W. Hsu Bamdad Hosseini H. Owhadi 43 0 0 02 Mar 2025
Fast Bayesian Optimization of Needle-in-a-Haystack Problems using Zooming Memory-Based Initialization (ZoMBI) Alexander E. Siemenn Zekun Ren Qianxiao Li Tonio Buonassisi 36 23 0 26 Aug 2022
AODisaggregation: toward global aerosol vertical profiles S. Bouabid D. Watson‐Parris Sofija Stefanović A. Nenes Dino Sejdinovic 24 0 0 06 May 2022
Nonnegative spatial factorization F. W. Townes Barbara E. Engelhardt 11 11 0 12 Oct 2021
GPflux: A Library for Deep Gaussian Processes Vincent Dutordoir Hugh Salimbeni Eric Hambro John Mcleod Felix Leibfried A. Artemev Mark van der Wilk J. Hensman M. Deisenroth S. T. John GP 33 23 0 12 Apr 2021
Bellman: A Toolbox for Model-Based Reinforcement Learning in TensorFlow John Mcleod Hrvoje Stojić Vincent Adam Dongho Kim Jordi Grau-Moya Peter Vrancx Felix Leibfried OffRL 21 2 0 26 Mar 2021
A Framework for Interdomain and Multioutput Gaussian Processes Mark van der Wilk Vincent Dutordoir S. T. John A. Artemev Vincent Adam J. Hensman 40 94 0 02 Mar 2020