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Hilbert Space Methods for Reduced-Rank Gaussian Process Regression

21 January 2014

Arno Solin

Simo Särkkä

Papers citing "Hilbert Space Methods for Reduced-Rank Gaussian Process Regression"

50 / 113 papers shown

Title
Linear Time Kernel Matrix Approximation via Hyperspherical Harmonics J. Ryan Anil Damle 48 0 0 08 Feb 2022
A Kernel-Based Approach for Modelling Gaussian Processes with Functional Information J. Nicholson P. Kiessler D. Brown GP 63 3 0 26 Jan 2022
When are Iterative Gaussian Processes Reliably Accurate? Wesley J. Maddox Sanyam Kapoor A. Wilson 69 10 0 31 Dec 2021
Stochastic Processes Under Linear Differential Constraints : Application to Gaussian Process Regression for the 3 Dimensional Free Space Wave Equation Iain Henderson P. Noble O. Roustant 47 1 0 23 Nov 2021
Contextual Bayesian optimization with binary outputs T. Fauvel M. Chalk 67 3 0 05 Nov 2021
Geometry-Aware Hierarchical Bayesian Learning on Manifolds Yonghui Fan Yalin Wang 33 2 0 30 Oct 2021
Periodic Activation Functions Induce Stationarity Lassi Meronen Martin Trapp Arno Solin BDL 84 21 0 26 Oct 2021
Efficient Exploration in Binary and Preferential Bayesian Optimization T. Fauvel M. Chalk 59 7 0 18 Oct 2021
GaussED: A Probabilistic Programming Language for Sequential Experimental Design Matthew A. Fisher Onur Teymur Chris J. Oates 87 1 0 15 Oct 2021
Efficient Fourier representations of families of Gaussian processes P. Greengard 77 3 0 28 Sep 2021
Low-rank statistical finite elements for scalable model-data synthesis Connor Duffin E. Cripps T. Stemler Mark Girolami 66 11 0 10 Sep 2021
Finite Element Representations of Gaussian Processes: Balancing Numerical and Statistical Accuracy D. Sanz-Alonso Ruiyi Yang 56 12 0 06 Sep 2021
Large-Scale Learning with Fourier Features and Tensor Decompositions Frederiek Wesel Kim Batselier 49 11 0 03 Sep 2021
Variational Inference at Glacier Scale D. Brinkerhoff BDL 51 11 0 16 Aug 2021
Efficient reduced-rank methods for Gaussian processes with eigenfunction expansions P. Greengard M. O’Neil 57 11 0 12 Aug 2021
Pathfinder: Parallel quasi-Newton variational inference Lu Zhang Bob Carpenter A. Gelman Aki Vehtari 132 41 0 09 Aug 2021
Wasserstein-Splitting Gaussian Process Regression for Heterogeneous Online Bayesian Inference Michael E. Kepler Alec Koppel Amrit Singh Bedi D. Stilwell 26 3 0 26 Jul 2021
Spectrum Gaussian Processes Based On Tunable Basis Functions Wenqi Fang Guanlin Wu Jingjing Li Ziyi Wang Jiang Cao Yang Ping 18 0 0 14 Jul 2021
Scalable Variational Gaussian Processes via Harmonic Kernel Decomposition Shengyang Sun Jiaxin Shi A. Wilson Roger C. Grosse BDL 31 7 0 10 Jun 2021
Gaussian Processes on Hypergraphs Thomas Pinder K. Turnbull Christopher Nemeth David Leslie 37 4 0 03 Jun 2021
Deep Neural Networks as Point Estimates for Deep Gaussian Processes Vincent Dutordoir J. Hensman Mark van der Wilk Carl Henrik Ek Zoubin Ghahramani N. Durrande BDL UQCV 103 31 0 10 May 2021
Sparse Algorithms for Markovian Gaussian Processes William J. Wilkinson Arno Solin Vincent Adam 62 12 0 19 Mar 2021
Temporal Gaussian Process Regression in Logarithmic Time Adrien Corenflos Zheng Zhao Simo Särkkä 60 3 0 19 Feb 2021
High-Dimensional Gaussian Process Inference with Derivatives Filip de Roos A. Gessner Philipp Hennig GP 56 17 0 15 Feb 2021
Gaussian Process Regression constrained by Boundary Value Problems Mamikon A. Gulian A. Frankel L. Swiler 72 25 0 22 Dec 2020
Pathwise Conditioning of Gaussian Processes James T. Wilson Viacheslav Borovitskiy Alexander Terenin P. Mostowsky M. Deisenroth 102 61 0 08 Nov 2020
Matérn Gaussian Processes on Graphs Viacheslav Borovitskiy I. Azangulov Alexander Terenin P. Mostowsky M. Deisenroth N. Durrande 51 82 0 29 Oct 2020
Stationary Activations for Uncertainty Calibration in Deep Learning Lassi Meronen Christabella Irwanto Arno Solin UQCV BDL 54 19 0 19 Oct 2020
Locally induced Gaussian processes for large-scale simulation experiments D. Cole R. Christianson R. Gramacy 70 21 0 28 Aug 2020
Convergence of Sparse Variational Inference in Gaussian Processes Regression David R. Burt C. Rasmussen Mark van der Wilk 82 74 0 01 Aug 2020
Orthogonally Decoupled Variational Fourier Features Dario Azzimonti Manuel Schürch A. Benavoli Marco Zaffalon 20 0 0 13 Jul 2020
Sparse Gaussian Processes with Spherical Harmonic Features Vincent Dutordoir N. Durrande J. Hensman 71 56 0 30 Jun 2020
Non-Stationary Multi-layered Gaussian Priors for Bayesian Inversion M. Emzir Sari Lasanen Z. Purisha L. Roininen Simo Särkkä 78 9 0 28 Jun 2020
Variational Orthogonal Features David R. Burt C. Rasmussen Mark van der Wilk BDL DRL 71 12 0 23 Jun 2020
Matérn Gaussian processes on Riemannian manifolds Viacheslav Borovitskiy Alexander Terenin P. Mostowsky M. Deisenroth 126 123 0 17 Jun 2020
A Survey of Constrained Gaussian Process Regression: Approaches and Implementation Challenges L. Swiler Mamikon A. Gulian A. Frankel Cosmin Safta J. Jakeman GP AI4CE 104 106 0 16 Jun 2020
Sparse Gaussian Process Based On Hat Basis Functions Wenqi Fang Huiyun Li Hui Huang Shaobo Dang Zhejun Huang Zheng Wang 8 1 0 15 Jun 2020
Scalable Thompson Sampling using Sparse Gaussian Process Models Sattar Vakili Henry B. Moss A. Artemev Vincent Dutordoir Victor Picheny 71 36 0 09 Jun 2020
Practical Hilbert space approximate Bayesian Gaussian processes for probabilistic programming Gabriel Riutort-Mayol Paul-Christian Bürkner Michael R. Andersen Arno Solin Aki Vehtari 84 72 0 23 Apr 2020
Consistent Online Gaussian Process Regression Without the Sample Complexity Bottleneck Alec Koppel Hrusikesha Pradhan K. Rajawat 34 32 0 23 Apr 2020
Gaussian Process Manifold Interpolation for Probabilistic Atrial Activation Maps and Uncertain Conduction Velocity Sam Coveney C. Corrado C. Roney D. O'Hare Steven E. Williams M. OÑeill Steven Niederer R. Clayton J. Oakley Richard D. Wilkinson 62 41 0 22 Apr 2020
A matrix-free approach to geostatistical filtering M. Pereira N. Desassis C. Magneron N. Palmer 23 1 0 06 Apr 2020
How Good are Low-Rank Approximations in Gaussian Process Regression? C. Daskalakis P. Dellaportas A. Panos 60 3 0 03 Apr 2020
Linearly Constrained Neural Networks J. Hendriks Carl Jidling A. Wills Thomas B. Schon 103 35 0 05 Feb 2020
Conjugate Gradients for Kernel Machines Simon Bartels Philipp Hennig 66 4 0 14 Nov 2019
Deep kernel learning for integral measurements Carl Jidling J. Hendriks Thomas B. Schon A. Wills 62 7 0 04 Sep 2019
The Use of Gaussian Processes in System Identification Simo Särkkä GP AI4TS 40 10 0 13 Jul 2019
Selecting the Metric in Hamiltonian Monte Carlo Benjamin B. Bales A. Pourzanjani Aki Vehtari Linda R. Petzold 39 6 0 28 May 2019
Neutron Transmission Strain Tomography for Non-Constant Stress-Free Lattice Spacing J. Hendriks Carl Jidling Thomas B. Schon A. Wills C. Wensrich E. Kisi 19 6 0 15 May 2019
Know Your Boundaries: Constraining Gaussian Processes by Variational Harmonic Features Arno Solin Manon Kok 71 23 0 10 Apr 2019