v1v2 (latest)

Variational Fourier features for Gaussian processes

21 November 2016

Arno Solin

Papers citing "Variational Fourier features for Gaussian processes"

50 / 138 papers shown

Title
From Local Interactions to Global Operators: Scalable Gaussian Process Operator for Physical Systems Sawan Kumar Tapas Tripura R. Nayek S. Chakraborty 5 0 0 18 Jun 2025
Constraint-Aware Diffusion Guidance for Robotics: Real-Time Obstacle Avoidance for Autonomous Racing Hao Ma Sabrina Bodmer Andrea Carron Melanie Zeilinger Michael Muehlebach 59 0 0 19 May 2025
Turbocharging Gaussian Process Inference with Approximate Sketch-and-Project Pratik Rathore Zachary Frangella Sachin Garg Shaghayegh Fazliani Michał Dereziński Madeleine Udell 55 0 0 19 May 2025
Optimal Bayesian Affine Estimator and Active Learning for the Wiener Model Sasan Vakili Manuel Mazo Jr. Peyman Mohajerin Esfahani 127 0 0 07 Apr 2025
Modeling Neural Activity with Conditionally Linear Dynamical Systems Victor Geadah Amin Nejatbakhsh David Lipshutz Jonathan W. Pillow Alex H. Williams AI4CE 285 0 0 25 Feb 2025
Computation-Aware Gaussian Processes: Model Selection And Linear-Time Inference Jonathan Wenger Kaiwen Wu Philipp Hennig Jacob R. Gardner Geoff Pleiss John P. Cunningham 84 7 0 01 Nov 2024
Gaussian Derivative Change-point Detection for Early Warnings of Industrial System Failures Hao Zhao Rong Pan 83 1 0 29 Oct 2024
Optimizing Posterior Samples for Bayesian Optimization via Rootfinding Taiwo A. Adebiyi Bach Do Ruda Zhang 200 2 0 29 Oct 2024
Latent mixed-effect models for high-dimensional longitudinal data Priscilla Ong Manuel Haußmann Otto Lönnroth Harri Lähdesmäki 42 0 0 17 Sep 2024
Review of Recent Advances in Gaussian Process Regression Methods Chenyi Lyu Xingchi Liu Lyudmila Mihaylova GP 52 3 0 12 Sep 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
Gaussian Processes Sampling with Sparse Grids under Additive Schwarz Preconditioner Haoyuan Chen Rui Tuo 62 0 0 01 Aug 2024
Adaptive RKHS Fourier Features for Compositional Gaussian Process Models Xinxing Shi Thomas Baldwin-McDonald Mauricio A. Álvarez 167 0 0 01 Jul 2024
Hyperparameter Optimization for Randomized Algorithms: A Case Study on Random Features Oliver R. A. Dunbar Nicholas H. Nelsen Maya Mutic 134 7 0 30 Jun 2024
Stein Random Feature Regression Houston Warren Rafael Oliveira Fabio Ramos BDL 92 0 0 01 Jun 2024
Future Aware Safe Active Learning of Time Varying Systems using Gaussian Processes Markus Lange-Hegermann Christoph Zimmer AI4TS 118 0 0 17 May 2024
Dynamic Online Ensembles of Basis Expansions Daniel Waxman Petar M. Djurić 93 5 0 02 May 2024
Fast Adaptive Fourier Integration for Spectral Densities of Gaussian Processes Paul G. Beckman Christopher J. Geoga 56 1 0 29 Apr 2024
Tensor Network-Constrained Kernel Machines as Gaussian Processes Frederiek Wesel Kim Batselier 118 0 0 28 Mar 2024
Hyperbolic Secant representation of the logistic function: Application to probabilistic Multiple Instance Learning for CT intracranial hemorrhage detection Francisco M. Castro-Macías Pablo Morales-Álvarez Yunan Wu Rafael Molina Aggelos K. Katsaggelos 23 2 0 21 Mar 2024
Kernel Multigrid: Accelerate Back-fitting via Sparse Gaussian Process Regression Lu Zou Liang Ding 78 0 0 20 Mar 2024
Efficiently Computable Safety Bounds for Gaussian Processes in Active Learning Jörn Tebbe Christoph Zimmer A. Steland Markus Lange-Hegermann Fabian Mies GP 74 3 0 28 Feb 2024
A General Theory for Kernel Packets: from state space model to compactly supported basis Liang Ding Rui Tuo 21 1 0 06 Feb 2024
Multi-modal Gaussian Process Variational Autoencoders for Neural and Behavioral Data Rabia Gondur Usama Bin Sikandar Evan Schaffer Mikio C. Aoi Stephen L. Keeley DRL 47 9 0 04 Oct 2023
Pointwise uncertainty quantification for sparse variational Gaussian process regression with a Brownian motion prior Luke Travis Kolyan Ray 59 4 0 29 Sep 2023
Convolutional Deep Kernel Machines Edward Milsom Ben Anson Laurence Aitchison BDL 96 5 0 18 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
Bayesian Non-linear Latent Variable Modeling via Random Fourier Features M. Zhang Gregory W. Gundersen Barbara Engelhardt BDL 25 2 0 14 Jun 2023
Spherical Inducing Features for Orthogonally-Decoupled Gaussian Processes Louis C. Tiao Vincent Dutordoir Victor Picheny BDL 50 0 0 27 Apr 2023
Actually Sparse Variational Gaussian Processes Harry Jake Cunningham Daniel Augusto R. M. A. de Souza So Takao Mark van der Wilk M. Deisenroth 89 7 0 11 Apr 2023
Free-Form Variational Inference for Gaussian Process State-Space Models Xuhui Fan Edwin V. Bonilla T. O’Kane Scott A. Sisson 66 9 0 20 Feb 2023
Scalable Gaussian Process Inference with Stan Till Hoffmann J. Onnela GP 35 4 0 21 Jan 2023
REDS: Random Ensemble Deep Spatial prediction Ranadeep Daw C. Wikle 39 10 0 09 Nov 2022
Ice Core Dating using Probabilistic Programming Aditya Ravuri Tom R. Andersson Ieva Kazlauskaite Will Tebbutt Richard Turner J. S. Hosking Neil D. Lawrence Markus Kaiser 27 0 0 29 Oct 2022
Equispaced Fourier representations for efficient Gaussian process regression from a billion data points P. Greengard M. Rachh A. Barnett 74 12 0 18 Oct 2022
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
Spectral Diffusion Processes Angus Phillips Thomas Seror M. Hutchinson Valentin De Bortoli Arnaud Doucet Emile Mathieu DiffM 132 17 0 28 Sep 2022
Deep Variational Implicit Processes Luis A. Ortega Simón Rodríguez Santana Daniel Hernández-Lobato BDL 63 5 0 14 Jun 2022
Generalized Variational Inference in Function Spaces: Gaussian Measures meet Bayesian Deep Learning Veit Wild Robert Hu Dino Sejdinovic BDL 131 13 0 12 May 2022
Causal Transformer for Estimating Counterfactual Outcomes Valentyn Melnychuk Dennis Frauen Stefan Feuerriegel CML 107 99 0 14 Apr 2022
Local Random Feature Approximations of the Gaussian Kernel Jonas Wacker Maurizio Filippone 89 5 0 12 Apr 2022
Modelling Non-Smooth Signals with Complex Spectral Structure W. Bruinsma Martin Tegnér Richard Turner 72 6 0 14 Mar 2022
Adaptive Cholesky Gaussian Processes Simon Bartels Kristoffer Stensbo-Smidt Pablo Moreno-Muñoz Wouter Boomsma J. Frellsen Søren Hauberg 78 3 0 22 Feb 2022
Variational Nearest Neighbor Gaussian Process Luhuan Wu Geoff Pleiss John P. Cunningham BDL 94 15 0 03 Feb 2022
Improved Random Features for Dot Product Kernels Jonas Wacker Motonobu Kanagawa Maurizio Filippone 57 8 0 21 Jan 2022
Efficient Hyperparameter Tuning for Large Scale Kernel Ridge Regression Giacomo Meanti Luigi Carratino Ernesto De Vito Lorenzo Rosasco 61 13 0 17 Jan 2022
Bridging the reality gap in quantum devices with physics-aware machine learning D. L. Craig H. Moon F. Fedele D. Lennon B. V. Straaten ... D. Zumbuhl G. Briggs Michael A. Osborne D. Sejdinovic N. Ares 63 15 0 22 Nov 2021
Spatio-Temporal Variational Gaussian Processes Oliver Hamelijnck William J. Wilkinson Niki A. Loppi Arno Solin Theodoros Damoulas AI4TS 72 35 0 02 Nov 2021