Papers citing 'Computation-Aware Kalman Filtering and Smoothing'

Title
Scalable Gaussian Processes with Latent Kronecker Structure Jihao Andreas Lin Sebastian Ament Maximilian Balandat David Eriksson José Miguel Hernández-Lobato E. Bakshy 43 3 0 07 Jun 2025
Randomised Postiterations for Calibrated BayesCG Niall Vyas Disha Hegde Jon Cockayne 124 0 0 05 Apr 2025
Learning to Solve Related Linear Systems Disha Hegde Jon Cockayne 132 0 0 21 Mar 2025
Online Conformal Probabilistic Numerics via Adaptive Edge-Cloud Offloading Qiushuo Hou Sangwoo Park Matteo Zecchin Yunlong Cai G. Yu Osvaldo Simeone 354 0 0 18 Mar 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 140 7 0 01 Nov 2024
Calibrated Computation-Aware Gaussian Processes Disha Hegde Mohamed Adil Jon Cockayne 120 5 0 11 Oct 2024
The Rank-Reduced Kalman Filter: Approximate Dynamical-Low-Rank Filtering In High Dimensions Jonathan Schmidt Philipp Hennig Jorg Nick Filip Tronarp 125 11 0 13 Jun 2023
Posterior and Computational Uncertainty in Gaussian Processes Jonathan Wenger Geoff Pleiss Marvin Pfortner Philipp Hennig John P. Cunningham 222 20 0 30 May 2022
Spatio-Temporal Variational Gaussian Processes Oliver Hamelijnck William J. Wilkinson Niki A. Loppi Arno Solin Theodoros Damoulas AI4TS 106 38 0 02 Nov 2021
Probabilistic Linear Solvers for Machine Learning Jonathan Wenger Philipp Hennig 124 17 0 19 Oct 2020
Fast Matrix Square Roots with Applications to Gaussian Processes and Bayesian Optimization Geoff Pleiss M. Jankowiak David Eriksson Anil Damle Jacob R. Gardner 103 45 0 19 Jun 2020
Efficiently Sampling Functions from Gaussian Process Posteriors James T. Wilson Viacheslav Borovitskiy Alexander Terenin P. Mostowsky M. Deisenroth 150 168 0 21 Feb 2020
Temporal Parallelization of Bayesian Smoothers Simo Särkkä Á. F. García-Fernández 236 41 0 30 May 2019
Learning Latent Dynamics for Planning from Pixels Danijar Hafner Timothy Lillicrap Ian S. Fischer Ruben Villegas David R Ha Honglak Lee James Davidson BDL 312 1,498 0 12 Nov 2018
Gaussian Processes and Kernel Methods: A Review on Connections and Equivalences Motonobu Kanagawa Philipp Hennig Dino Sejdinovic Bharath K. Sriperumbudur GP BDL 188 353 0 06 Jul 2018
Efficient Spatio-Temporal Gaussian Regression via Kalman Filtering M. Todescato Andrea Carron R. Carli G. Pillonetto Luca Schenato 76 27 0 03 May 2017
Bayesian Probabilistic Numerical Methods Jon Cockayne Chris J. Oates T. Sullivan Mark Girolami 163 168 0 13 Feb 2017
On dimension reduction in Gaussian filters A. Solonen Tiangang Cui J. Hakkarainen Youssef Marzouk 74 22 0 26 Aug 2015
Probabilistic Numerics and Uncertainty in Computations Philipp Hennig Michael A. Osborne Mark Girolami 123 310 0 03 Jun 2015
Probabilistic Interpretation of Linear Solvers Philipp Hennig 110 107 0 10 Feb 2014
Infinite-dimensional Bayesian filtering for detection of quasi-periodic phenomena in spatio-temporal data Arno Solin Simo Särkkä 119 24 0 11 Mar 2013