Spatio-Temporal Variational Gaussian Processes

2 November 2021

Oliver Hamelijnck

William J. Wilkinson

Niki A. Loppi

Arno Solin

Theodoros Damoulas

AI4TS

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Papers citing "Spatio-Temporal Variational Gaussian Processes"

22 / 22 papers shown

Title
Computation-Aware Kalman Filtering and Smoothing Marvin Pfortner Jonathan Wenger Jon Cockayne Philipp Hennig 86 3 0 13 Mar 2025
Revisiting Kernel Attention with Correlated Gaussian Process Representation Long Minh Bui Tho Tran Huu Duy-Tung Dinh T. Nguyen Trong Nghia Hoang 52 2 0 27 Feb 2025
Diffusion-aware Censored Gaussian Processes for Demand Modelling Filipe Rodrigues DiffM 64 0 0 21 Jan 2025
Physics-Informed Variational State-Space Gaussian Processes Oliver Hamelijnck Arno Solin Theodoros Damoulas 31 0 0 20 Sep 2024
Scalable Multi-Output Gaussian Processes with Stochastic Variational Inference Xiaoyu Jiang Sokratia Georgaka Magnus Rattray Mauricio A. Alvarez 26 0 0 02 Jul 2024
Scalable Spatiotemporal Prediction with Bayesian Neural Fields Feras A. Saad Jacob Burnim Colin Carroll Brian Patton Urs Köster Rif A. Saurous Matthew Hoffman BDL AI4TS AI4CE 27 6 0 12 Mar 2024
eXponential FAmily Dynamical Systems (XFADS): Large-scale nonlinear Gaussian state-space modeling Matthew Dowling Yuan Zhao Il Memming Park BDL 30 5 0 03 Mar 2024
Gaussian Processes for Monitoring Air-Quality in Kampala Clara Stoddart Lauren Shrack Richard Sserunjogi Usman Abdul-Ganiy Engineer Bainomugisha Deo Okure Ruth Misener Jose Pablo Folch Ruby Sedgwick 14 1 0 28 Nov 2023
Informative path planning for scalar dynamic reconstruction using coregionalized Gaussian processes and a spatiotemporal kernel Lorenzo Booth Stefano Carpin 18 2 0 13 Sep 2023
Multi-Robot Informative Path Planning from Regression with Sparse Gaussian Processes (with Appendix) Kalvik Jakkala Srinivas Akella 19 8 0 13 Sep 2023
Sequential Monte Carlo Learning for Time Series Structure Discovery Feras A. Saad Brian Patton Matt Hoffman Rif A. Saurous Vikash K. Mansinghka AI4TS 21 9 0 13 Jul 2023
Deep Gaussian Markov Random Fields for Graph-Structured Dynamical Systems Fiona Lippert Bart Kranstauber E. E. V. Loon Patrick Forré BDL AI4CE 9 0 0 14 Jun 2023
The Rank-Reduced Kalman Filter: Approximate Dynamical-Low-Rank Filtering In High Dimensions Jonathan Schmidt Philipp Hennig Jorg Nick Filip Tronarp 20 9 0 13 Jun 2023
Linear Time GPs for Inferring Latent Trajectories from Neural Spike Trains Matthew Dowling Yuan Zhao Il Memming Park 20 6 0 01 Jun 2023
Actually Sparse Variational Gaussian Processes Harry Jake Cunningham Daniel Augusto R. M. A. de Souza So Takao Mark van der Wilk M. Deisenroth 24 5 0 11 Apr 2023
Integrated Nested Laplace Approximations for Large-Scale Spatial-Temporal Bayesian Modeling Lisa Gaedke-Merzhäuser E. Krainski R. Janalík H. Rue Olaf Schenk 11 2 0 27 Mar 2023
Efficient Sensor Placement from Regression with Sparse Gaussian Processes in Continuous and Discrete Spaces Kalvik Jakkala Srinivas Akella 21 1 0 28 Feb 2023
Short-term Prediction and Filtering of Solar Power Using State-Space Gaussian Processes Sean Nassimiha Peter Dudfield Jack Kelly M. Deisenroth So Takao 16 1 0 01 Feb 2023
Markovian Gaussian Process Variational Autoencoders Harrison Zhu Carles Balsells Rodas Yingzhen Li BDL AI4TS 38 14 0 12 Jul 2022
Bayes-Newton Methods for Approximate Bayesian Inference with PSD Guarantees William J. Wilkinson Simo Särkkä Arno Solin BDL 21 15 0 02 Nov 2021
Uncertainty Quantification and Experimental Design for Large-Scale Linear Inverse Problems under Gaussian Process Priors Cédric Travelletti D. Ginsbourger N. Linde 14 3 0 08 Sep 2021
Temporal Parallelization of Bayesian Smoothers Simo Särkkä Á. F. García-Fernández 133 39 0 30 May 2019