Blitzkriging: Kronecker-structured Stochastic Gaussian Processes

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Blitzkriging: Kronecker-structured Stochastic Gaussian Processes

27 October 2015

Michael A. Osborne

Stephen J. Roberts

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Papers citing "Blitzkriging: Kronecker-structured Stochastic Gaussian Processes"

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Title
Low-rank computation of the posterior mean in Multi-Output Gaussian Processes Sebastian Esche Martin Stoll 67 0 0 30 Apr 2025
Tensor network square root Kalman filter for online Gaussian process regression Clara Menzen Manon Kok Kim Batselier 25 0 0 05 Sep 2024
Federated Bayesian Neural Regression: A Scalable Global Federated Gaussian Process Hao Yu Kaiyang Guo Mahdi Karami Xi Chen Guojun Zhang Pascal Poupart FedML 76 3 0 13 Jun 2022
The Renyi Gaussian Process: Towards Improved Generalization Xubo Yue Raed Al Kontar 129 3 0 15 Oct 2019
Kernel Conditional Density Operators Ingmar Schuster Mattes Mollenhauer Stefan Klus Krikamol Muandet 82 26 0 27 May 2019
Banded Matrix Operators for Gaussian Markov Models in the Automatic Differentiation Era N. Durrande Vincent Adam L. Bordeaux Stefanos Eleftheriadis J. Hensman 68 26 0 26 Feb 2019
Battery health prediction under generalized conditions using a Gaussian process transition model R. Richardson Michael A. Osborne David A. Howey 34 186 0 17 Jul 2018
Scalable Gaussian Processes with Grid-Structured Eigenfunctions (GP-GRIEF) Trefor W. Evans P. Nair GP 42 25 0 05 Jul 2018
When Gaussian Process Meets Big Data: A Review of Scalable GPs Haitao Liu Yew-Soon Ong Xiaobo Shen Jianfei Cai GP 133 697 0 03 Jul 2018
Standing Wave Decomposition Gaussian Process Chi-Ken Lu Scott Cheng-Hsin Yang Patrick Shafto 16 2 0 09 Mar 2018
Scalable Gaussian Processes with Billions of Inducing Inputs via Tensor Train Decomposition Pavel Izmailov Alexander Novikov D. Kropotov 87 62 0 19 Oct 2017
Variational Fourier features for Gaussian processes J. Hensman N. Durrande Arno Solin VLM 93 202 0 21 Nov 2016
Stochastic Variational Deep Kernel Learning A. Wilson Zhiting Hu Ruslan Salakhutdinov Eric Xing BDL 129 267 0 01 Nov 2016
Nested Kriging predictions for datasets with large number of observations D. Rullière N. Durrande François Bachoc C. Chevalier 67 67 0 19 Jul 2016