Bayesian Filtering

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Overview

Bayesian filtering studies how to update beliefs about hidden states as new observations arrive, which supports reliable prediction and decision-making when measurements are noisy or incomplete. Kalman and Gaussian filters offer efficient updates for roughly unimodal beliefs, while particle, ensemble, and variational methods handle nonlinear or non-Gaussian systems; newer approaches also use learned proposals, score models, and generative flows. These methods are used in robotics, target tracking, navigation, and large-scale data assimilation, where both accurate state estimates and calibrated uncertainty matter. A central challenge is balancing computational cost and scalability against the ability to represent complex posterior distributions, especially in high-dimensional systems with sparse observations or changing dynamics.

Latest papers

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56 papers6 papers in the last four weeks, down 33% on the four weeks before. 0.0% of all new papers.

  1. SURGE: Approximation and Training Free Particle Filter for Diffusion Surrogate

    May 18, 2026Lifu Wei, Yinuo Ren, Naichen Shi +1Particle FilteringBayesian Filtering

    Department of Mechanical Engineering, Northwestern University, Evanston, IL, United States · Institute for Computational & Mathematical Engineering, Stanford University, Stanford, CA, United States · Department of Industrial Engineering & Management Sciences, Northwestern University, Evanston, IL, United States

  2. The Score Kalman Filter

    May 15, 2026Kaito Iwasaki, Anthony Bloch, Taeyoung Lee +1Kalman FilteringBayesian Filtering

    Department of Mathematics University of Michigan · Department of Mechanical and Aerospace Engineering George Washington University · Department of Naval Architecture & Marine Engineering and Department of Robotics University of Michigan

  3. Coupling-Informed Transport Maps for Bayesian Filtering in Nonlinear Dynamical Systems

    May 13, 2026Dengfei Zeng, Lijian Jiang, Shuyu Sun +1Dynamical SystemsSimulation-Based Inference

    School of Mathematical Sciences, Tongji University, Shanghai, 200092 China · School of Mathematical Sciences, Tongji University, Shanghai, 200092 China, Key Laboratory of Intelligent Computing and Applications (Ministry of Education), Tongji University, Shanghai, 200092 China

  4. Precision Tracked Transformer via Kalman Filtering, Kriging and Process Noise

    May 12, 2026Bo Long, Deepak Agarwal, Jelena Markovic-Voronov +2Bayesian FilteringTransformer

    LinkedIn Core AI

  5. Online Bayesian Calibration under Gradual and Abrupt System Changes

    May 7, 2026Yang Xu, Chiwoo ParkParticle FilteringBayesian Filtering

    Department of Industrial and Systems Engineering University of Washington Seattle, WA 98195

  6. Natural Gradient Bayesian Filtering: Geometry-Aware Filter for Dynamical Systems

    May 4, 2026Chang Liu, Wenhan Cao, Zeju Sun +8Bayesian FilteringRobot State Estimation

    School of Advanced Manufacturing and Robotics, Peking University, China. · School of Vehicle and Mobility, Tsinghua University, China. · Beijing Institute of Mathematical Sciences and Applications (BIMSA), China. +3

  7. Learning Discriminators for Resampling in the Ensemble Gaussian Mixture Filter through a Normalizing Flow Approach

    May 1, 2026Zain Jabbar, Andrey A. PopovParticle FilteringBayesian Filtering

  8. Robust volatility updates for Hierarchical Gaussian Filtering

    May 1, 2026Christoph Mathys, Nicolas Legrand, Peter Thestrup Waade +2Bayesian FilteringHierarchical Bayesian Modeling

    Interacting Minds Centre, Aarhus University, 8000 Aarhus C, Denmark · Centre for Humanities Computing, Aarhus University, 8000 Aarhus C, Denmark · Translational Neuromodeling Unit, University of Zurich & ETH Zurich, 8032 Zurich, Switzerland +1

  9. Breaking the Communication-Accuracy Trade-off: A Sparsified Information Diffusion Framework for Multi-Agent Collaborative Perception

    May 1, 2026Jirong Zha, Chenyu Zhao, Nan Zhou +5Bayesian FilteringCooperative Perception

    Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China · Shenzhen Institute of Artificial Intelligence and Robotics, Shenzhen, China, 518000 · Shenzhen Smart City Technology Development Group, Shenzhen, China, 518000

  10. SNGR: Selective Non-Gaussian Refinement for Ambiguous SLAM Factor Graphs

    Apr 23, 2026Anushka Kulkarni, Sarthak DubeySimultaneous Localization and MappingFactor Graph Optimization

    Northeastern University, Boston, MA, USA

  11. Natural Gradient Gaussian Approximation Filter on Lie Groups for Robot State Estimation

    Apr 11, 2026Tianyi Zhang, Wenhan Cao, Chang Liu +2Robot State EstimationBayesian Filtering

    School of Vehicle and Mobility, Tsinghua University, Beijing, China · College of Engineering, Peking University, Beijing, China · School of Vehicle and Mobility and College of Artificial Intelligence, Tsinghua University, Beijing, China

  12. A Machine Learning Framework for Turbofan Health Estimation via Inverse Problem Formulation

    Apr 9, 2026Milad Leyli-Abadi, Lucas Thil, Sebastien Razakarivony +2Predictive MaintenanceBayesian Inverse Problems

    Institut de recherche technologique SystemX, Palaiseau, France · École Polytechnique, LIX, Palaiseau, France · Safran Tech, Magny-les-Hameaux, France

  13. Amortized Filtering and Smoothing with Conditional Normalizing Flows

    Apr 8, 2026Tiangang Cui, Xiaodong Feng, Chenlong Pei +2Bayesian FilteringData Assimilation

    School of Mathematics and Statistics, The University of Sydney, Camperdown, NSW 2006, Australia · Institute of Advanced Study, Beijing Normal-Hong Kong Baptist University, Zhuhai 519087, China · SKLMS & Institute of Computational Mathematics and Scientific/Engineering Computing, Academy of Mathematics and Systems Science, Chinese Academy of Sciences +1

  14. Rethinking Forward Processes for Score-Based Nonlinear Data Assimilation in High Dimensions

    Apr 3, 2026Eunbi Yoon, Won Chang, Donghan Kim +1Data AssimilationBayesian Filtering

    KAIST · Seoul National University

  15. Cross-Modal Visuo-Tactile Object Perception

    Apr 2, 2026Anirvan Dutta, Simone Tasciotti, Claudia Cusseddu +6Visuo-Tactile Representation LearningUncertainty-Aware Multimodal Fusion

    BMW Group AG, München, Germany. · Department of Bioengineering, Imperial College of Science, Technology and Medicine, London, UK. · Department of Biology, University of Crete, Heraklion, Greece. +7

  16. Bayesian Learning-Enhanced Navigation with Deep Smoothing for Inertial-Aided Navigation

    Mar 26, 2026Nadav Cohen, Itzik KleinInertial NavigationBayesian Filtering

    N. Cohen and I. Klein are with the Hatter Department of Marine Technologies, Charney School of Marine Sciences, University of Haifa, Israel.

  17. Autoregressive Guidance of Deep Spatially Selective Filters using Bayesian Tracking for Efficient Extraction of Moving Speakers

    Mar 24, 2026Jakob Kienegger, Timo GerkmannBayesian FilteringDirection-of-Arrival Estimation

    Signal Processing Group, Department of Informatics, University of Hamburg, 22527 Hamburg, Germany

  18. ModTrack: Sensor-Agnostic Multi-View Tracking via Identity-Informed PHD Filtering with Covariance Propagation

    Mar 16, 2026Aditya Iyer, Jack Roberts, Nora AyanianMulti-Object TrackingUncertainty-Aware Multimodal Fusion

    Department of Computer Science, Brown University, Providence, RI, USA · School of Engineering, Brown University, Providence, RI, USA

  19. B2^2F-Map: Crowd-sourced Mapping with Bayesian B-spline Fusion

    Mar 2, 2026Yiping Xie, Yuxuan Xia, Erik Stenborg +5HD Map ConstructionBayesian Filtering

    Zenseact, Lindholmspiren 2, Gothenburg, Sweden. · Department of Electrical Engineering, Linköping University, Linköping, Sweden. · Yuxuan Xia was a Post-doc with Zenseact, and he is now with the Department of Automation and Perception, Shanghai Jiao Tong University, Shanghai, China. +1

  20. Physics-informed neural particle flow for the Bayesian update step

    Feb 26, 2026Domonkos Csuzdi, Tamás Bécsi, Olivér TörőParticle FilteringBayesian Filtering

  21. A Comparison of Bayesian Prediction Techniques for Mobile Robot Trajectory Tracking

    Feb 17, 2026Jose Luis Peralta-Cabezas, Miguel Torres-Torriti, Marcelo Guarini-HermannRobot Trajectory TrackingRobot State Estimation

    Dept. of Electrical Engineering, Pontificia Universidad Católica de Chile, Vicuña Mackenna 4860, Casilla 306-22, Santiago, Chile

  22. Recursive Entropic Variational Inference for Nonlinear State-Space Models

    Nov 19, 2025Hany Abdulsamad, Ángel F. García-Fernández, Simo SärkkäBayesian FilteringVariational Inference

    Amsterdam Machine Learning Lab University of Amsterdam, Netherlands · Information Processing and Telecommunications Center Universidad Politécnica de Madrid, Spain · ELLIS Institute Finland Department of Electrical Engineering and Automation Aalto University, Finland

  23. A Sliding-Window Filter for Online Continuous-Time Continuum Robot State Estimation

    Oct 30, 2025Spencer Teetaert, Sven Lilge, Jessica Burgner-Kahrs +1Robot State EstimationBayesian Filtering

    University of Toronto Robotics Institute, Toronto, ON, Canada

  24. PyDPF: A Python Package for Differentiable Particle Filtering

    Oct 29, 2025John-Joseph Brady, Benjamin Cox, Yunpeng Li +1Particle FilteringBayesian Filtering

    King’s College London · Max-Planck Institut für Physik · University of Edinburgh

  25. Flow Matching for Efficient and Scalable Data Assimilation

    Aug 18, 2025Taos Transue, Bohan Chen, So Takao +1Flow MatchingKalman Filtering

    Department of Mathematics and Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT, 84112 · The Computing and Mathematical Sciences Department, California Institute of Technology, 1200 E California Blvd, Pasadena, CA 91125

  26. The Constitutional Filter: Bayesian Estimation of Compliant Agents

    Dec 24, 2024Simon Kohaut, Felix Divo, Benedict Flade +3Bayesian FilteringNeuro-Symbolic Reasoning

    Artificial Intelligence and Machine Learning Group, Department of Computer Science, TU Darmstadt, 64283 Darmstadt, Germany · Honda Research Institute Europe GmbH, Carl-Legien-Str. 30, 63073 Offenbach, Germany · Uncertainty in Artificial Intelligence Group, Department of Mathematics and Computer Science, TU Eindhoven, 5600 MB Eindhoven, Netherlands +3