Computation-Aware Kalman Filtering and Smoothing

International Conference on Artificial Intelligence and Statistics (AISTATS), 2024

13 March 2025

Papers citing "Computation-Aware Kalman Filtering and Smoothing"

22 / 22 papers shown

Title
Bayesian Natural Gradient Fine-Tuning of CLIP Models via Kalman Filtering Hossein Abdi Mingfei Sun Wei Pan VLM 205 0 0 03 Nov 2025
Scalable Gaussian Processes with Latent Kronecker Structure Jihao Andreas Lin Sebastian Ament Maximilian Balandat David Eriksson José Miguel Hernández-Lobato E. Bakshy 155 3 0 07 Jun 2025
Randomised Postiterations for Calibrated BayesCG Niall Vyas Disha Hegde Jon Cockayne 299 0 0 05 Apr 2025
Learning to Solve Related Linear Systems Disha Hegde Jon Cockayne 240 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 622 0 0 18 Mar 2025
Computation-Aware Gaussian Processes: Model Selection And Linear-Time InferenceNeural Information Processing Systems (NeurIPS), 2024 Jonathan Wenger Kaiwen Wu Philipp Hennig Jacob R. Gardner Geoff Pleiss John P. Cunningham 312 9 0 01 Nov 2024
Calibrated Computation-Aware Gaussian ProcessesInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2024 Disha Hegde Mohamed Adil Jon Cockayne 212 5 0 11 Oct 2024
The Rank-Reduced Kalman Filter: Approximate Dynamical-Low-Rank Filtering In High DimensionsNeural Information Processing Systems (NeurIPS), 2023 Jonathan Schmidt Philipp Hennig Jorg Nick Filip Tronarp 261 14 0 13 Jun 2023
Posterior and Computational Uncertainty in Gaussian ProcessesNeural Information Processing Systems (NeurIPS), 2022 Jonathan Wenger Geoff Pleiss Marvin Pfortner Philipp Hennig John P. Cunningham 501 21 0 30 May 2022
Spatio-Temporal Variational Gaussian ProcessesNeural Information Processing Systems (NeurIPS), 2021 Oliver Hamelijnck William J. Wilkinson Niki A. Loppi Arno Solin Theodoros Damoulas AI4TS 179 47 0 02 Nov 2021
Probabilistic Linear Solvers for Machine LearningNeural Information Processing Systems (NeurIPS), 2020 Jonathan Wenger Philipp Hennig 207 18 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 211 45 0 19 Jun 2020
Efficiently Sampling Functions from Gaussian Process PosteriorsInternational Conference on Machine Learning (ICML), 2020 James T. Wilson Viacheslav Borovitskiy Alexander Terenin P. Mostowsky M. Deisenroth 306 177 0 21 Feb 2020
Temporal Parallelization of Bayesian SmoothersIEEE Transactions on Automatic Control (IEEE TAC), 2019 Simo Särkkä Á. F. García-Fernández 304 48 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 635 1,631 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 248 382 0 06 Jul 2018
Efficient Spatio-Temporal Gaussian Regression via Kalman Filtering M. Todescato Andrea Carron R. Carli G. Pillonetto Luca Schenato 144 29 0 03 May 2017
Bayesian Probabilistic Numerical MethodsSIAM Review (SIAM Rev.), 2017 Jon Cockayne Chris J. Oates T. Sullivan Mark Girolami 283 173 0 13 Feb 2017
On dimension reduction in Gaussian filters A. Solonen Tiangang Cui J. Hakkarainen Youssef Marzouk 126 24 0 26 Aug 2015
Probabilistic Numerics and Uncertainty in ComputationsProceedings of the Royal Society A (Proc. R. Soc. A), 2015 Philipp Hennig Michael A. Osborne Mark Girolami 187 319 0 03 Jun 2015
Probabilistic Interpretation of Linear SolversSIAM Journal on Optimization (SIAM J. Optim.), 2014 Philipp Hennig 187 109 0 10 Feb 2014
Infinite-dimensional Bayesian filtering for detection of quasi-periodic phenomena in spatio-temporal data Arno Solin Simo Särkkä 167 24 0 11 Mar 2013