Spatial Mapping with Gaussian Processes and Nonstationary Fourier Features

15 November 2017

Jean-François Ton

Seth Flaxman

Dino Sejdinovic

Samir Bhatt

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Papers citing "Spatial Mapping with Gaussian Processes and Nonstationary Fourier Features"

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Title
A Guide to Bayesian Optimization in Bioprocess Engineering Maximilian Siska Emma Pajak Katrin Rosenthal Antonio del Rio Chanona E. Lieres L. M. Helleckes 120 0 0 14 Aug 2025
Nonstationary Sparse Spectral Permanental ProcessNeural Information Processing Systems (NeurIPS), 2024 Zicheng Sun Yixuan Zhang Zenan Ling Xuhui Fan Feng Zhou 164 1 0 04 Oct 2024
Non-stationary and Sparsely-correlated Multi-output Gaussian Process with Spike-and-Slab PriorINFORMS Journal on Data Science (JIDS), 2024 Wang Xinming Li Yongxiang Yue Xiaowei Wu Jianguo 210 0 0 05 Sep 2024
Stein Random Feature Regression Houston Warren Rafael Oliveira Fabio Ramos BDL 308 0 0 01 Jun 2024
Trigonometric Quadrature Fourier Features for Scalable Gaussian Process RegressionInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2023 Kevin Li Max Balakirsky Simon Mak 197 3 0 23 Oct 2023
Numerically Stable Sparse Gaussian Processes via Minimum Separation using Cover TreesJournal of machine learning research (JMLR), 2022 Alexander Terenin David R. Burt A. Artemev Seth Flaxman Mark van der Wilk C. Rasmussen Hong Ge 199 7 0 14 Oct 2022
Fast and Scalable Adversarial Training of Kernel SVM via Doubly Stochastic GradientsAAAI Conference on Artificial Intelligence (AAAI), 2021 Huimin Wu Zhengmian Hu Bin Gu AAML 90 10 0 21 Jul 2021
The Inductive Bias of Quantum KernelsNeural Information Processing Systems (NeurIPS), 2021 Jonas M. Kubler Simon Buchholz Bernhard Schölkopf 242 140 0 07 Jun 2021
Transferring model structure in Bayesian transfer learning for Gaussian process regressionKnowledge-Based Systems (KBS), 2021 Milan Papez A. Quinn 130 13 0 18 Jan 2021
Gauss-Legendre Features for Gaussian Process RegressionJournal of machine learning research (JMLR), 2021 Paz Fink Shustin H. Avron GP 264 14 0 04 Jan 2021
Reducing the Variance of Variational Estimates of Mutual Information by Limiting the Critic's Hypothesis Space to RKHSInternational Conference on Pattern Recognition (ICPR), 2020 P. A. Sreekar Ujjwal Tiwari A. Namboodiri 104 2 0 17 Nov 2020
Sparse Spectrum Warped Input Measures for Nonstationary Kernel LearningNeural Information Processing Systems (NeurIPS), 2020 A. Tompkins Rafael Oliveira F. Ramos 211 6 0 09 Oct 2020
Implicit Kernel AttentionAAAI Conference on Artificial Intelligence (AAAI), 2020 Kyungwoo Song Yohan Jung Dongjun Kim Il-Chul Moon 251 17 0 11 Jun 2020
Random Features for Kernel Approximation: A Survey on Algorithms, Theory, and Beyond Fanghui Liu Xiaolin Huang Yudong Chen Johan A. K. Suykens BDL 465 188 0 23 Apr 2020
Convolutional Spectral Kernel LearningArtificial Intelligence (AIJ), 2020 Jian Li Yong Liu Weiping Wang BDL 84 5 0 28 Feb 2020
$π$ VAE: a stochastic process prior for Bayesian deep learning with MCMC Swapnil Mishra Seth Flaxman Tresnia Berah Harrison Zhu Mikko S. Pakkanen Samir Bhatt BDL 186 4 0 17 Feb 2020
Scalable Hybrid HMM with Gaussian Process Emission for Sequential Time-series Data Clustering Yohan Jung Jinkyoo Park 157 3 0 07 Jan 2020
Automated Spectral Kernel LearningAAAI Conference on Artificial Intelligence (AAAI), 2019 Jian Li Yong Liu Weiping Wang 121 14 0 11 Sep 2019
Spatial Analysis Made Easy with Linear Regression and Kernels Philip Milton E. Giorgi Samir Bhatt 145 22 0 22 Feb 2019
Neural Non-Stationary Spectral Kernel Sami Remes Markus Heinonen Samuel Kaski BDL 145 10 0 27 Nov 2018