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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
Improved Regret Bounds for Gaussian Process Upper Confidence Bound in Bayesian Optimization Shogo Iwazaki GP 39 0 0 02 Jun 2025
Assessing Quantum Advantage for Gaussian Process Regression Dominic Lowe M.S. Kim Roberto Bondesan 5 1 0 28 May 2025
Efficient Deconvolution in Populational Inverse Problems Arnaud Vadeboncoeur Mark Girolami Andrew M. Stuart 35 0 0 26 May 2025
Geometry-aware Active Learning of Spatiotemporal Dynamic Systems Xizhuo Zhang AI4CE 93 0 0 26 Apr 2025
Constrained Gaussian Process Motion Planning via Stein Variational Newton Inference Jiayun Li Kay Pompetzki An T. Le Haolei Tong Jan Peters Georgia Chalvatzaki 74 0 0 07 Apr 2025
Efficient Transformed Gaussian Process State-Space Models for Non-Stationary High-Dimensional Dynamical Systems Zhidi Lin Ying Li Feng Yin Juan Maroñas Alexandre Thiéry 160 0 0 24 Mar 2025
Provable Quantum Algorithm Advantage for Gaussian Process Quadrature Cristian A. Galvis-Florez Ahmad Farooq Simo Särkkä 77 0 0 20 Feb 2025
Kalman Filter-Based Distributed Gaussian Process for Unknown Scalar Field Estimation in Wireless Sensor Networks Jaemin Seo Geunsik Bae H. Oh 58 0 0 09 Feb 2025
When the whole is greater than the sum of its parts: Scaling black-box inference to large data settings through divide-and-conquer Emily C. Hector Amanda Lenzi 429 1 0 31 Dec 2024
IDF-MFL: Infrastructure-free and Drift-free Magnetic Field Localization for Mobile Robot Hongming Shen Zhenyu Wu Wei Wang Qiyang Lyu Huiqin Zhou Danwei W. Wang 57 1 0 09 Nov 2024
Optimizing Posterior Samples for Bayesian Optimization via Rootfinding Taiwo A. Adebiyi Bach Do Ruda Zhang 200 2 0 29 Oct 2024
Gaussian Process Thompson Sampling via Rootfinding Taiwo A. Adebiyi Bach Do Ruda Zhang GP 83 3 0 10 Oct 2024
Latent mixed-effect models for high-dimensional longitudinal data Priscilla Ong Manuel Haußmann Otto Lönnroth Harri Lähdesmäki 47 0 0 17 Sep 2024
Statistical Finite Elements via Interacting Particle Langevin Dynamics Alex Glyn-Davies Connor Duffin Ieva Kazlauskaite Mark Girolami O. Deniz Akyildiz 85 0 0 11 Sep 2024
Tensor network square root Kalman filter for online Gaussian process regression Clara Menzen Manon Kok Kim Batselier 28 0 0 05 Sep 2024
Adaptive Basis Function Selection for Computationally Efficient Predictions Anton Kullberg Frida Marie Viset Isaac Skog Gustaf Hendeby 55 0 0 14 Aug 2024
Exploiting Hankel-Toeplitz Structures for Fast Computation of Kernel Precision Matrices Frida Viset Anton Kullberg Frederiek Wesel Arno Solin 104 0 0 05 Aug 2024
Efficient Patient Fine-Tuned Seizure Detection with a Tensor Kernel Machine S. J. D. Rooij Frederiek Wesel B. Hunyadi AAML 49 0 0 01 Aug 2024
The GeometricKernels Package: Heat and Matérn Kernels for Geometric Learning on Manifolds, Meshes, and Graphs P. Mostowsky Vincent Dutordoir I. Azangulov Noémie Jaquier Michael John Hutchinson Aditya Ravuri Leonel Rozo Alexander Terenin Viacheslav Borovitskiy 76 6 0 10 Jul 2024
Dynamic Online Ensembles of Basis Expansions Daniel Waxman Petar M. Djurić 93 5 0 02 May 2024
Supporting Bayesian modelling workflows with iterative filtering for multiverse analysis Anna Elisabeth Riha Nikolas Siccha Antti Oulasvirta Aki Vehtari 59 0 0 02 Apr 2024
Towards Multilevel Modelling of Train Passing Events on the Staffordshire Bridge L. Bull Chiho Jeon Mark Girolami Andrew Duncan Jennifer Schooling Miguel Bravo Haro 44 0 0 26 Mar 2024
Twenty ways to estimate the Log Gaussian Cox Process model with point and aggregated case data: the rts2 package for R Samuel I Watson 26 1 0 14 Mar 2024
Quantum-Assisted Hilbert-Space Gaussian Process Regression Ahmad Farooq Cristian A. Galvis-Florez Simo Särkkä 16 5 0 01 Feb 2024
Ensemble Kalman Filtering Meets Gaussian Process SSM for Non-Mean-Field and Online Inference Zhidi Lin Yiyong Sun Feng Yin Alexandre Thiéry 65 4 0 10 Dec 2023
Projecting basis functions with tensor networks for Gaussian process regression Clara Menzen Eva Memmel Kim Batselier Manon Kok 108 2 0 31 Oct 2023
Discussing the Spectrum of Physics-Enhanced Machine Learning; a Survey on Structural Mechanics Applications M. Haywood-Alexander Wei Liu Kiran Bacsa Zhilu Lai Eleni Chatzi AI4CE 42 12 0 31 Oct 2023
Large-scale magnetic field maps using structured kernel interpolation for Gaussian process regression Clara Menzen Marnix Fetter Manon Kok 52 1 0 25 Oct 2023
Implicit Gaussian process representation of vector fields over arbitrary latent manifolds Robert L. Peach M. Vinao-Carl Nir Grossman Michael David Emma-Jane Mallas David Sharp Paresh A. Malhotra P. Vandergheynst Adam Gosztolai 88 5 0 28 Sep 2023
Out of Distribution Detection via Domain-Informed Gaussian Process State Space Models Alonso Marco Elias Morley Claire Tomlin 88 3 0 13 Sep 2023
Quantized Fourier and Polynomial Features for more Expressive Tensor Network Models Frederiek Wesel Kim Batselier 55 1 0 11 Sep 2023
Integrated Variational Fourier Features for Fast Spatial Modelling with Gaussian Processes Talay M Cheema C. Rasmussen GP 122 2 0 27 Aug 2023
Neural Orientation Distribution Fields for Estimation and Uncertainty Quantification in Diffusion MRI W. Consagra L. Ning Yogesh Rathi MedIm 19 9 0 16 Jul 2023
Exploring Model Misspecification in Statistical Finite Elements via Shallow Water Equations Connor Duffin P. Branson M. Rayson Mark Girolami E. Cripps T. Stemler 8 0 0 11 Jul 2023
Rao-Blackwellized Particle Smoothing for Simultaneous Localization and Mapping Manon Kok Arno Solin Thomas B. Schon 43 6 0 06 Jun 2023
Gaussian Processes with State-Dependent Noise for Stochastic Control Marcel Menner K. Berntorp 41 3 0 25 May 2023
Stochastic PDE representation of random fields for large-scale Gaussian process regression and statistical finite element analysis Kim Jie Koh F. Cirak AI4CE 58 12 0 23 May 2023
Learning battery model parameter dynamics from data with recursive Gaussian process regression A. Aitio Dominik Jöst D. Sauer David A. Howey 36 5 0 26 Apr 2023
Learning-Based Optimal Control with Performance Guarantees for Unknown Systems with Latent States Robert Lefringhausen Supitsana Srithasan Armin Lederer Sandra Hirche 71 6 0 31 Mar 2023
Generalised Linear Mixed Model Specification, Analysis, Fitting, and Optimal Design in R with the glmmr Packages S. Watson 36 4 0 22 Mar 2023
Bayesian Kernelized Tensor Factorization as Surrogate for Bayesian Optimization Mengying Lei Lijun Sun 44 1 0 28 Feb 2023
Gaussian Process-Gated Hierarchical Mixtures of Experts Yuhao Liu Marzieh Ajirak Petar M. Djurić MoE 50 1 0 09 Feb 2023
Spatially scalable recursive estimation of Gaussian process terrain maps using local basis functions Frida Marie Viset Rudy Helmons Manon Kok 96 1 0 17 Oct 2022
Geostatistics for large datasets on Riemannian manifolds: a matrix-free approach M. Pereira N. Desassis D. Allard 26 10 0 26 Aug 2022
Physics-informed machine learning for Structural Health Monitoring E. Cross S. Gibson M. R. Jones D. J. Pitchforth S. Zhang T. Rogers AI4CE 102 36 0 30 Jun 2022
Orthonormal Expansions for Translation-Invariant Kernels Filip Tronarp Toni Karvonen VLM 479 1 0 17 Jun 2022
Scalable Computations for Nonstationary Gaussian Processes Paul G. Beckman Christopher J. Geoga Michael L. Stein M. Anitescu 13 4 0 10 Jun 2022
Constraining Gaussian processes for physics-informed acoustic emission mapping Matthew R. Jones T. Rogers E. Cross AI4CE 75 16 0 03 Jun 2022
Indoor SLAM Using a Foot-mounted IMU and the local Magnetic Field Mostafa Osman Frida Marie Viset Manon Kok 63 6 0 29 Mar 2022
Adjoint-aided inference of Gaussian process driven differential equations Paterne Gahungu Christopher W. Lanyon Mauricio A. Alvarez Engineer Bainomugisha M. Smith Richard D. Wilkinson 57 5 0 09 Feb 2022