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. Normalizing Flow for Neural-Enhanced Track-Before-Detect

    Oct 18, 2026Shaoxiu Wei, Bhaskar Rao, Florian MeyerMulti-Object TrackingBayesian Filtering

    University of California San Diego, La Jolla, CA

  2. What Do Foundation Models for Market Microstructure Learn? A Controlled Study with Synthetic Limit Order Books

    Oct 14, 2026Fernando AceroLimit Order Book ModelingTime-Series Foundation Models

    J.P. Morgan QTR AI Research, United Kingdom

  3. Variational Filtering for Bayesian Last Layers with an Independent Binary Probit Surrogate

    Oct 12, 2026Dimitrije Markovic, Conor Heins, Alexander Tschantz +1Bayesian Neural NetworksBayesian Inference

    Independent Researcher Vienna, Austria · Independent Researcher Berlin, Germany · University of Sussex Brighton, UK +1

  4. BAT3R: Robust Online 3D Reconstruction with Bayesian Adaptive State Updates

    Oct 12, 2026Lijian Li, Yuanpeng He, Yudian Zheng +6Streaming 3D ReconstructionBayesian Filtering

    University of Macau, Macau SAR, China · School of Computer Science, Peking University, Beijing, China · Key Laboratory of High Confidence Software Technologies (Peking University), Ministry of Education, Beijing, China

  5. Voltic: Distinguishing Volatility from Stochasticity in Recurrent Memory

    Oct 5, 2026Parsa Hejabi, Morteza Dehghani, Payam PirayKalman FilteringBayesian Filtering

    University of Southern California

  6. LD-EnFF: Latent-Dynamics Ensemble Flow Filtering for Data Assimilation with Sparse Observations

    Oct 2, 2026Ziyu Tian, Kaichen Shen, Wenbo Hao +3Data AssimilationBayesian Filtering

    School of Mathematics, Georgia Institute of Technology · School of Computational Science and Engineering, Georgia Institute of Technology

  7. AECSF: Adaptive Ensemble Conditional Score Filtering for High-Dimensional Nonlinear Data Assimilation

    Sep 26, 2026Yangwen Zhang, Shiwei Ni, Xiaoping Zhang +2Data AssimilationBayesian Filtering

    School of Mathematical Sciences, Tongji University, Shanghai 200092, China · Department of Information and Computational Sciences, Wuhan University, Wuhan 430072, China · Department of Mathematics, University of South Carolina, Columbia, South Carolina 29208, USA

  8. Online Learning via Learned Latent Bayesian Tracking

    Sep 25, 2026Guy Gerson, Tomer Raviv, Nir Shlezinger +2Online LearningBayesian Filtering

    School of ECE Ben-Gurion University Be‘er-Sheva, Israel · Institute for Intelligent Networked Systems (INSI) Northeastern University London London, U.K

  9. Learning to Bias: Machine Learning-Enhanced Particle Filters

    Sep 24, 2026Apoorv Srivastava, Eric DarveParticle FilteringBayesian Filtering

    Stanford University Stanford, CA 94305

  10. Full-Covariance Smoothing of Bayesian Neural Networks for Online Adaptation

    Sep 23, 2026Oren Wright, Haoming Jing, Qiaoan Shen +3Bayesian Neural NetworksBayesian Filtering

    Department of Electrical and Computer Engineering, Carnegie Mellon University · Software Engineering Institute, Carnegie Mellon University · Fujitsu Research of America

  11. Bayesian Filtering in Physical Systems via Test-time Trained Flow Matching

    Sep 20, 2026Ruiqi Feng, Chongyi Wang, Tao Zhang +1Flow MatchingBayesian Filtering

    Westlake University & Zhejiang University · Westlake University

  12. FREESIA: Covariance-Aware Posterior Transport for Expressive and Scalable Data Assimilation

    Sep 19, 2026Shiwei Ni, Yangwen Zhang, Hang Qi +2Data AssimilationBayesian Filtering

    School of Mathematical Sciences, Tongji University, Shanghai, China · Department of Mathematics, University of South Carolina, Columbia, SC 29208, USA

  13. Causal neural set filtering for online multi-target tracking

    Sep 13, 2026Zhongdi Liu, Huangyu DaiMulti-Object TrackingBayesian Filtering

    Hangzhou Applied Acoustics Research Institute, Hangzhou 310023, China · Independent Researcher, Hangzhou, China

  14. How Wrong Can a Good Predictor Be? Diverging Updates with Vanishing Predictive KL

    Sep 10, 2026Qifu Wen, Shuaijun Liu, Zihan Zhou +2Bayesian FilteringHidden Markov Models

    Boston University, Boston, MA, USA · Shanghai Jiao Tong University, Shanghai, China · The Hong Kong University of Science and Technology (Guangzhou), Guangzhou, China

  15. Multi-robot Learning-based Informative Path Planning Using Spatio-Temporal Gaussian Process Kalman Filter

    Aug 31, 2026Muqing Cao, Yunwoo Lee, Junbin Yuan +2Informative Path PlanningBayesian Filtering

    Robotics Institute, Carnegie Mellon University, Pittsburgh, USA. · Engineering Systems and Design Pillar, Singapore University of Technology and Design, Singapore. · Department of Electrical Engineering and Computer Science, Daegu Gyeongbuk Institute of Science and Technology, Daegu, South Korea.

  16. Quanta Perception as Probabilistic Events

    Aug 27, 2026Varun Sundar, Pavan Thodima, Sacha Jungerman +1Robotic PerceptionEvent-Based Vision

    Department of Computer Sciences, University of Wisconsin–Madison, Wisconsin, United States.

  17. IMMNet: Hybrid Fusion of Model-based and Data-driven Approaches for Maneuvering Target Tracking

    Jul 15, 2026Yixuan Zhao, Chaoqun Yang, Lin Gao +2Bayesian Filtering

    School of Automation, Southeast University, Nanjing, 210096, China · School of ICE, University of Electronic Science and Technology of China, Chengdu, 611731, China · Faculty of Artificial Intelligence, Shanghai University of Electric Power, Shanghai, 201300, China +1

  18. Dynamic Online Processor-Native Inference for State Estimation

    Jul 13, 2026Orestis KaparounakisParticle FilteringBayesian Filtering

  19. Chalito: An Extensible Library for Filtering-Based State Estimation in Quadruped Robots

    Jul 10, 2026Hilton Marques Souza Santana, João Carlos Virgolino Soares, Marco Antonio Meggiolaro +1Bayesian FilteringRobot State Estimation

    Department of Mechanical Engineering at the Pontifical Catholic University of Rio de Janeiro · Dynamic Legged Systems Lab, Istituto Italiano di Tecnologia

  20. Tensorized algorithms and scalable filtering methods for hidden Markov and factorial hidden Markov models

    Jul 8, 2026Roxana Barrios, Ioannis SgouralisBayesian FilteringSequence Modeling

    Department of Mathematics, University of Tennessee, Knoxville, TN

  21. QANTIS: Hardware-Calibrated Sequential POMDP Belief Updates on IBM Heron

    Jul 7, 2026Bayram Yuksel Eker, Suayb S. Arslan, Ozgur Nazli +2Belief-Space PlanningBayesian Filtering

    Neura Parse Ltd. London, United Kingdom · Dept. of Computer Engineering Boğaziçi University Istanbul, Turkey · Dept. of Physics Izmir University of Economics Izmir, Turkey +2

  22. Message Passing Based Two-Timescale Bayesian Learning for Joint Channel and Memory Hardware Impairments Tracking

    Jul 2, 2026Wei Xu, An LiuBayesian FilteringChannel Estimation

    College of Information Science and Electronic Engineering, Zhejiang University, Hangzhou 310027, China

  23. A Bayesian Filtering Approach for Learning Lagrangian Dynamics from Noisy Measurements

    Jun 30, 2026Kundan Kumar, Shreya Das, Simo SärkkäBayesian FilteringNonlinear System Identification

    K. Kumar is with the School of Engineering and Applied Science, Ahmedabad University, India · K. Kumar and S. Särkkä are with the ELLIS Institute Finland and the Department of Electrical Engineering and Automation, Aalto University, Finland · S. Das is with the Department of Electrical Engineering, Indian Institute of Technology (BHU) Varanasi, India

  24. Learning Probabilistic Filters with Strictly Proper Scoring Rules

    Jun 25, 2026Eviatar Bach, Ricardo Baptista, Jochen Bröcker +2Bayesian FilteringData Assimilation

    Department of Meteorology, University of Reading Brian Hoskins Building, Reading, RG6 6ET, UK · Department of Mathematics and Statistics, University of Reading Pepper Lane, Reading, RG6 6AX, UK · National Centre for Earth Observation Brian Hoskins Building, University of Reading, Reading, RG6 6ET, UK +2

  25. Structured Noise Adaptation for Sequential Bayesian Filtering with Embedded Latent Transfer Operators

    Jun 12, 2026Naichang Ke, Pongpisit Thanasutives, Yoshinobu KawaharaKalman FilteringBayesian Filtering

    The University of Osaka · RIKEN Center for Advanced Intelligence Project (AIP)

  26. Computation-Aware Kalman Filtering with Model Selection for Neural Dynamics

    May 31, 2026JR Huml, Jonathan Wenger, John P. CunninghamDynamical SystemsBayesian Filtering

    Department of Statistics, Columbia University; Zyphra Technologies · Department of Statistics, Columbia University; Zuckerman Institute

  27. Memory by Design: Bayesian Layers for Sequence Modeling

    May 29, 2026Matthew Dowling, Hyungju Jeon, Cristina Savin +1Long-Context RetrievalBayesian Filtering

    Champalimaud Research, Champalimaud Foundation, Portugal · Center for Neural Science, New York University, USA · Center for Data Science, New York University, USA

  28. Prefix-Safe Bayesian Belief Tracking for LLM Reasoning Reliability:Separating Calibration from Ranking

    May 26, 2026Zhenghan Song, Yunyi Li, Yulong LiuBayesian FilteringLanguage Model Calibration

    Cornell University · Columbia University

  29. A Semantic and Occlusion-Aware GM-PHD Filter

    May 20, 2026Jovan Menezes, Mark CampbellBayesian FilteringAutonomous Driving Perception

    Sibley School of Mechanical and Aerospace Engineering, Cornell University, Ithaca, NY, USA

  30. Training-Free Bayesian Filtering with Generative Emulators

    May 19, 2026Thomas Savary, François Rozet, Gilles LouppeParticle FilteringBayesian Filtering

    SAIL, Montefiore institute, University of Liège, Belgium.