Bayesian Neural Networks

Also known as BNN

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Overview

Bayesian neural networks study how to represent uncertainty in a network’s predictions by placing distributions over its weights or functions, helping distinguish uncertainty from limited data from noise inherent in the data. Common approaches include variational inference, Monte Carlo dropout, Laplace approximations, Hamiltonian Monte Carlo and stochastic-gradient MCMC, with structured priors and Bayesian last layers used to reduce computation. Researchers evaluate these methods on tasks such as UCI regression, image classification and out-of-distribution detection, language-model adaptation, and scientific or clinical forecasting, often measuring calibration as well as accuracy. A central challenge is obtaining reliable, informative uncertainty at practical cost: approximate posteriors can be under-calibrated or miss important correlations, while sampling and benchmark results can vary substantially across methods and settings.

Latest papers

CardsList

94 papers10 papers in the last four weeks, up 67% on the four weeks before. 0.1% of all new papers.

  1. Gibbs Variational Last Layers for Long-Horizon Dynamics Learning

    Nov 2, 2026Paul Brunzema, Henrik Hose, Sebastian TrimpeProbabilistic Time Series ForecastingBayesian Neural Networks

    RWTH Aachen University, Aachen, Germany

  2. BASILISC: Bayesian Alignment of Siamese-Integrated Latents for Inferring Single-cell Correspondence

    Oct 28, 2026Sepideh Saran, Mahsa Ghanbari, Uwe OhlerCross-Modal AlignmentMulti-Omics Data Integration

    The Berlin Institute for Medical Systems Biology, Max Delbrück Center for Molecular Medicine, Germany · Department of Electrical Engineering and Computer Science, Technical University of Berlin, Germany · Department of Biology, Humboldt University of Berlin, Germany +1

  3. Modular Bayesian Foundation Models: Bayesian time series encoders for OOD detection, routing and forecasting

    Oct 28, 2026Mame Diarra Toure, Quang Hung Pham, Mohamed Ryad Zemouri +3Time-Series Foundation ModelsModular Neural Networks

    Department of Mathematics and Statistics McGill University · Hydro-Quebec

  4. Prior Predictive Matching for Bayesian LoRA

    Oct 26, 2026Tomasz Kuśmierczyk, Eliezer de Souza da Silva, Marcin SenderaBayesian LoRABayesian Neural Networks

  5. Sparse Bayesian Neural Networks via Sticky Piecewise Deterministic Markov Processes

    Oct 23, 2026August Arnstad, Geir Olve Storvik, Filippo Pagani +1Bayesian Neural NetworksSparse Neural Networks

    Department of Mathematics, University of Oslo, NO · Department of Statistics, University of Warwick, UK

  6. Bayesian Neural Networks via Dirichlet Process Priors on the Data-Generating Distribution for Randomized Value Functions in Deep Reinforcement Learning

    Oct 20, 2026Sumit VashishthaBayesian RLUncertainty Estimation in RL

    Independent Researcher

  7. Theoretical and Practical Advances in Hierarchical Bayesian Deep Learning Methodology

    Oct 13, 2026Neil K. Chada, Simon Cotter, Kody J. H. Law +1Bayesian Neural NetworksHierarchical Bayesian Modeling

    Department of Mathematics, City University of Hong Kong, Hong Kong SAR. · School of Mathematics, University of Manchester, UK.

  8. 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

  9. When Has a Bayesian Neural Network Sampled Enough? Adaptive Inference Time with Statistical Guarantees

    Oct 8, 2026Fabian Denoodt, Sibylle HessAdaptive SamplingBayesian Neural Networks

    Eindhoven University of Technology

  10. Sparsifying Stochasticity, Not Capacity: Partial Stochasticity via Deep Weight Factorization of Prior Scales

    Oct 7, 2026Marius P Linhard, Maurizio FilipponeBayesian Neural NetworksConditional Distribution Estimation

    Université Grenoble Alpes, France · KAUST, Saudi Arabia

  11. The Impact of Likelihood Tempering on the Limiting Predictive Moments of Variational Bayesian Linear Neural Networks

    Oct 6, 2026Ian Zhang, Thibault RandrianarisoaBayesian Neural NetworksVariational Inference

    Department of Statistical Sciences, University of Toronto · Dunlap Institute for Astronomy and Astrophysics

  12. 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

  13. Bayesian classification of astronomical spectra with class uncertainties

    Sep 18, 2026Simon Barton, Martin Sahlén, Andreas Korn +1Monte Carlo DropoutMulticlass Classification

    Theoretical Astrophysics, Division of Astronomy and Space Physics, Department of Physics and Astronomy, Uppsala University, Box 524, 751 20 Uppsala, Sweden. · Observational Astrophysics, Division of Astronomy and Space Physics, Department of Physics and Astronomy, Uppsala University, Box 524, 751 20 Uppsala, Sweden · Division of High Energy Physics, Department of Physics and Astronomy, Uppsala University, Box 524, 751 20 Uppsala, Sweden +1

  14. Certified Uncertainty Propagation in One-Shot Federated Bayesian Models via Posterior Event Transport

    Sep 14, 2026Mahyar Mohammadi, Mohammad Hossein Badiei, Abolfazl Yaghmaei +1Bayesian Neural NetworksNeural Network Verification

    School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, 1417614411, Iran · School of Computer Science, Institute for Research in Fundamental Sciences (IPM), P.O. Box 19395-5746, Tehran, Iran

  15. Online Bayesian Node Classification on Inductive Graphs under Distribution Shift

    Sep 12, 2026Jinwen Xu, Gonzalo Mateos Buckstein, Qin LuNode ClassificationGraph Neural Networks

    School of Electrical and Computer Engineering, University of Georgia, Athens, GA, USA · Department of Electrical and Computer Engineering, University of Rochester, Rochester, NY, USA

  16. 4D Parallelism Unlocks Exascale Bayesian Neural Networks for High-Fidelity Atmospheric Modeling

    Sep 11, 2026Deifilia Kieckhefen, Juan Pedro Gutiérrez Hermosillo Muriedas, Lars Helge Heyen +12Bayesian Neural NetworksUncertainty Quantification

    Karlsruhe Institute of Technology, Germany · Forschungszentrum Jülich, Germany · CSC – IT Center for Science Ltd., Finnland +1

  17. HiBRIDGE: A Hierarchical Bayesian Neural Network Framework for Interpretable Dialogue Management in Group-Robot Interaction

    Sep 8, 2026Massimiliano Nigro, Hatice Gunes, Micol Spitale +1Bayesian Neural NetworksHuman-Robot Interaction

    Department of Electronics, Information and Bioengineering, Politecnico di Milano, Italy · Affective Intelligence and Robotics (AFAR) Lab, Department of Computer Science and Technology, University of Cambridge, UK

  18. More accurate behavioral predictions with hybrid Bayesian-connectionist models

    Aug 23, 2026Brenden M. Lake, Akshay K. Jagadish, Guangyuan JiangComputational Cognitive ModelingHuman Behavior Modeling

    Departments of Computer Science and Psychology, Princeton University · Princeton AI Lab, Princeton University · Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology

  19. Hidden Axis of Uncertainty: Latent-Posterior Alignment in Graph Neural Networks with Bayesian Output Layers

    Aug 21, 2026Suk Hoon Choi, Damdae Park, Junhyuk Choi +4Bayesian Neural NetworksGraph Neural Networks

    Clean Energy Research Center, Korea Institute of Science and Technology, Seoul 02792, Republic of Korea. · Department of Chemical and Biological Engineering, Korea University, Seoul 02841, Republic of Korea. · Division of Energy & Environment Technology, Korea University of Science and Technology, 217 Gajeong-ro, Yuseong-gu, Daejeon 34113, Republic of Korea.

  20. Comment on "Modeling rapid language learning by distilling Bayesian priors into artificial neural networks"

    Aug 13, 2026Orr Well, Idan Tarshish, Nur Lan +1Bayesian Neural NetworksMeta-Learning

    1Tel Aviv University · 2École Normale Supérieure

  21. Uncertainty-Aware Deep Learning for Genomics Applications: Insights from an Empirical Study

    Aug 11, 2026Sepideh Saran, Mahsa Ghanbari, Uwe OhlerBayesian Neural NetworksUncertainty Quantification

    The Berlin Institute for Medical Systems Biology, Max Delbrück Center for Molecular Medicine, Germany · Department of Electrical Engineering and Computer Science, Technical University of Berlin, Germany · Department of Biology, Humboldt University of Berlin, Germany +1

  22. Constrained Co-Design for Photonic Bayesian Neural Networks

    Aug 3, 2026Hendrik Borras, Xiao Wang, Bernhard Klein +4Bayesian Neural NetworksUncertainty Quantification

    Hardware and Artificial Intelligence Lab, Institute of Computer Engineering, Heidelberg University, Germany · Neuromorphic Quantumphotonics Kirchhoff-Institute for Physics, Heidelberg University, Germany

  23. Uncertainty quantification for trustworthy deep learning: Methods and measures

    Jul 30, 2026H. Martin Gillis, Thomas TrappenbergBayesian Neural NetworksUncertainty Quantification

    Faculty of Computer Science, Dalhousie University, Halifax, Nova Scotia, Canada

  24. Rethinking Likelihood distributions: Student's t Likelihood Boosts Bayesian Neural Network Performance

    Jul 28, 2026Pei-Hsuan Hsia, Lars H. Heyen, Arvid Weyrauch +4Bayesian Neural NetworksBayesian Inference

    Scientific Computing Center, Karlsruhe Institute of Technology · Scientific Computing Center, Karlsruhe Institute of Technology; and Helmholtz AI

  25. Guiding Posterior Exploration with Optimizer-Derived Geometry

    Jul 28, 2026Moritz Schlager, Emanuel Sommer, Thomas Möllenhoff +1Bayesian Neural NetworksMarkov Chain Monte Carlo

    TUM, MCML · LMU Munich, MCML · RIKEN AIP

  26. DP-IVON-Gradsq: Differentially Private Squared-Gradient Improved Variational Online Newton

    Jul 26, 2026Nour Jamoussi, Ikram Dridi, Giuseppe Serra +1Bayesian Neural NetworksPrivacy-Preserving ML

    EURECOM, Sophia Antipolis, France · Concordia University, Montreal, Canada · University of Granada, Granada, Spain

  27. Neural Feature Governance: Extending Atom Prevalence

    Jul 23, 2026Idris Karel Seunda Ekwe, Patrick Tenga Shako, Ernest Parfait FokouéBayesian Neural NetworksUncertainty Quantification

    African Institute for Mathematical Sciences (AIMS), Cameroon · Rochester Institute of Technology (RIT), US

  28. Disentangling Model and Human Data Uncertainty in Apparent Facial Age Estimation

    Jul 17, 2026Andrei Foitos, Ivo Pascal de Jong, Matias Valdenegro-ToroBayesian Neural NetworksUncertainty Quantification

    Bernoulli Institute, University of Groningen, Groningen, NL

  29. Width-Robust Learnability in Mean-Field Bayesian Neural Networks

    Jul 7, 2026Dmitry Vaintrob, Kaarel HänniBayesian Neural NetworksNeural Network Generalization

    Principles of Intelligence

  30. Uncertainty-Aware Last-Layer Adaptation of RETFound for Referable Diabetic Retinopathy Screening Under Dataset Shift

    Jun 30, 2026Karim MardhaniBayesian Neural NetworksDistribution Shift Robustness

    University of Colorado Boulder Boulder, CO, USA