Bayesian

Follow this topic Ask about this topic

Recent momentum

+0%

37 papers in the last 28 days · 0.6% of indexed attention

Twelve weeks of publication activity for this topic as it is defined today.

Weekly history

Recent digests

What was published in this topic, kept on the site without email delivery.

Period ending 2026-09-21

17 new papers

A weekly snapshot of new work published in Bayesian.

Period ending 2026-09-14

5 new papers

A weekly snapshot of new work published in Bayesian.

Period ending 2026-09-07

7 new papers

A weekly snapshot of new work published in Bayesian.

387 papers

Latest in Bayesian

Browse all topics →

A solvable model for unsupervised federated learning
Jun 11, 2026Giovanni Catania, Aurélien Decelle, Gianluca Manzan +2Federated Learning Distributional Learning
Towards Provably Fair Machine Learning: Bayesian Approaches For Consistent and Transparent Predictions
Jun 10, 2026Owen O'Neill, Fintan CostelloFairness-Aware Learning Subgroup Information
Phase Transitions in Attention: A Bayesian Theory of Copy Head Emergence
Jun 10, 2026Itay Lavie, Kirsten Fischer, Andrey Lekov +3Phase Transitions Emergence
Population-Aware Physics-Informed Neural Particle Flow for Bayesian Update
Jun 9, 2026Batu Candan, Simone ServadioConventional Physics-Informed Neural Networks Physical Dynamics
Information-Preserving Continuous Occupancy Mapping with Variance-Weighted Submap Joining
Jun 9, 2026Zhuhua Bai, Yingyu Wang, Liang Zhao +1Simultaneous Localization And Mapping 3D Semantic Occupancy Prediction
In-Context Learning for Latent Space Bayesian Optimization
Jun 8, 2026Tuan A. Vu, Harri Lähdesmäki, Julien MartinelliBayesian Optimization Molecular Optimization
Bayesian Selective Latent Inference for Wastewater-First Influenza Monitoring
Jun 8, 2026Yixuan Zhang, Yang Song, Hao Wang +2Epidemic Forecasting Bayesian
Bridged SBI: Correcting Biased Low-Fidelity Posteriors for Cost-Efficient High-Fidelity Inference
Jun 8, 2026Gahee Kim, Yuki Kadokawa, Sandro M. Alcantara Tacora +5Posterior Bayesian
Hierarchical Projection for Adaptive Knowledge Transfer
Jun 7, 2026Samhita Pal, Tian GuCross-Task Knowledge Transfer Transfer Learning
Improving Bayesian Optimization via Training-Aware Conditional Diffusion Models
Jun 7, 2026Yilin Zheng, Haowei Wang, Szu Hui Ng +1Bayesian Optimization Bayesian
Structure-Preserving Correction Learning for Sparse Bayesian Inference in Brain Source Imaging
Jun 5, 2026Marco Morik, Xiao Ruiting, Shinichi Nakajima +2Electroencephalography Spatial Super-Resolution Neuroimaging Models
HARP: Efficient Data Selection for Finetuning Large Language Models
Jun 5, 2026Ning Wang, Zhengxin Zhang, Maosen Tang +3Model Selection Downstream Reasoning
Synthics: Synthetic Physics-like Datasets for Machine Learning
Jun 4, 2026Jari VepsäläinenSynthetic Data Symbolic Regression
PAC-Bayesian Adversarially Robust Generalization for Message Passing Graph Neural Networks: A Sensitivity Analysis
Jun 4, 2026Ziling Liang, Xinping Yi, Qingsong Wen +1Graph Neural Networks Message Passing Neural Networks
Discrete Causal Representations from Heterogeneous Domains: A Bayesian Approach with Social Survey Applications
Jun 4, 2026Ankur Garg, Michael Stettler, Aaron Schein +1Causal Representation Learning Subspace Intervention Framework
LMT: A Bayesian Framework for Causal Discovery from Textual Alarm Records in Manufacturing Systems
Jun 3, 2026Xiaofeng Xiao, Jianhong Chen, Qiuzhuang Sun +2Causal Foundation Models Early Warning
Generalized TV-- $\ell_p$ Structured Priors for Bayesian $T_1$ Mapping
Jun 3, 2026Disi Lin, Martin Berggren, Tommy LöfstedtSpatial Priors Bayesian
Environment-Robust Representation Learning with Empirical Bayes
Jun 3, 2026Yuli Slavutsky, Matthew Shen, Bohan Wu +1Bayesian Latent Variable
In-Context Graphical Inference
Jun 3, 2026Zehua Cheng, Wei Dai, Jiahao SunProbabilistic Inference Bayesian
Bayesian learning for the stochastic shortest path problem
Jun 3, 2026Chon Wai Ho, Sumeetpal S. Singh, Jiaqi GuoMarkov Decision Processes Bayesian
BayaHAR: Lightweight Bayesian Few-Shot User Adaptation for On-Device Personalized Human Activity Recognition
Jun 3, 2026Maximilian Burzer, Till Riedel, Michael Beigl +1Human Activity Recognition Parameter-Efficient Adaptation
Neural Galerkin Normalizing Flows for Bayesian Inference of Diffusions with Inaccessible Boundaries
Jun 3, 2026Riccardo Saporiti, Fabio NobileStochastic Differential Equations Fokker--Planck Equation
APIC: Amortized Physics-Informed Calibration using Neural Processes
Jun 2, 2026Aishwarya Venkataramanan, Sai Karthikeya Vemuri, Joachim DenzlerPhysics-Informed Machine Learning Calibrated Uncertainty
Bayes-Sufficient Representations in Supervised Learning
Jun 2, 2026Vasileios SevetlidisBayesian Supervised Learning
Bayesian Tensor Decomposition with Diffusion Model Prior
Jun 2, 2026Zerui Tao, Qibin ZhaoDiffusion Priors Low-Rank Factorization
Local Preferential Bayesian Optimization
Jun 1, 2026Johanna Menn, Miriam Kober, Paul Brunzema +2Bayesian Optimization Parallel Continuous Local Search
ShaplEIG: Bayesian Experimental Design for Shapley Value Estimation
Jun 1, 2026David Rundel, Fabian Fumagalli, Maximilian Muschalik +2Shapley Value Bayesian Experimental Design
Bayesian meta-learning for modeling Alzheimer's disease progression
Jun 1, 2026Clara Hoffmann, Nadja KleinAlzheimer Meta-Learning
Flow-Transformed Implicit Processes for Function-Space Variational Inference
Jun 1, 2026Luis A. Ortega, Andrés R. Masegosa, Thomas D. NielsenVariational Inference Bayesian
MINTS: Minimalist Thompson Sampling
Jun 1, 2026Kaizheng WangThompson Sampling Multi-Armed Bandits
Uncertainty-Calibrated Diffusion for Reliable 3D Molecular Graph Generation
Jun 1, 2026Fang Wan, Jingxiang Qu, Yi LiuMolecular Generation Molecular Graphs
Sample Complexity and Decision-Theoretic Guarantees for Bayesian Model Averaging over Decision Trees with Catalan-Exponential Priors
May 31, 2026Livija Jakaite, Vitaly SchetininDecision Trees Bayesian
Soft-NBCE: Entropy-Weighted Chunk Fusion for Long-Context
May 31, 2026Shihao Ji, Mingyu Li, Zihui SongEfficient Long-Context Inference Bayesian
AnyEdit++: Adaptive Long-Form Knowledge Editing via Bayesian Surprise
May 31, 2026Bowen Tian, Caixue He, Jiemin Wu +4Multimodal Knowledge Editing Long-Form Generation
Optimal-Point Variance Reduction For Bayesian Optimization With Regret Guarantee
May 31, 2026Shion TakenoBayesian Optimization Variance Reduction
Bandit Simulation for Average Reward Inference
May 30, 2026Samya Praharaj, Chih-Yu Chang, Koulik Khamaru +1Confidence Intervals Bandits
Bayesian Inference of Nonlinear Malaria Dynamics in Ghana via an Ensemble Markov Chain Monte Carlo Sampler
May 30, 2026T. Ansah-Narh, Y. Asare Afrane, J. Bremang TandohMalaria Bayesian
Annotation-Informed Block-Sparse Bayesian Modeling for cis-Expression Prediction
May 30, 2026Lei Huang, Hui Shen, Kuan-Jui Su +9Genomics Logistic Regression
Auditing Near-Optimal Policies Can Be Exponentially Hard: Conditional Query Lower Bounds via Occupancy Rashomon Capacity
May 29, 2026Ibne Farabi Shihab, Sanjeda Akter, Anuj SharmaAlgorithm Auditing Optimal Policies
Point-in-Time Financial RAG with Frozen LLMs and Market-Feedback Adaptive Retrieval
May 29, 2026Zijie Zhao, Roy E. WelschFinance Domain Deepseek
Memory by Design: Probabilistic Sequence Layers
May 29, 2026Matthew Dowling, Hyungju Jeon, Cristina Savin +1Recurrent Model Bayesian
Scalable Bayesian Inference for Nonlinear Conservation Laws
May 29, 2026Tim Weiland, Philipp HennigReliable Uncertainty Quantification Ill-Posed Inverse Problem
Bayesian Inference with Shaped Deep Non-linear MLPs
May 29, 2026Boris Hanin, Tianze JiangBayesian Neural Networks Bayesian
AbstainGNN: Teaching Graph Neural Networks to Abstain for Graph Classification
May 29, 2026Xixun Lin, Zhiheng Zhou, Zhengyin Zhang +9Graph Neural Networks Abstention
iLoRA: Bayesian Low-Rank Adaptation with Latent Interaction Graphs for Microbiome Diagnosis
May 28, 2026Yang Song, Yixuan Zhang, Lingfa Meng +5Low-Rank Adaptation Bacterial Colony Counting
Joint Model and Data Sparsification via the Marginal Likelihood
May 28, 2026Alexander Timans, Thomas Möllenhoff, Christian A. Naesseth +2Sparse Recovery Sparsity
Certified Policy Optimisation for Nested Causal Bandits via PAC-Bayes Risk
May 28, 2026Tim Woydt, Paul-David ZuercherOptimal Policies Thompson Sampling
Kernel Renormalization in Bayesian Deep Neural Networks: the Equivalent Wishart Ansatz in the Proportional Regime
May 28, 2026Paolo Baglioni, Christian Keup, Vincenzo Zimbardo +4Bayesian Neural Networks Renormalization Group
On the Construction and Implications of Low-Loss Valleys in LoRA-based Bayesian Inference
May 28, 2026Daniel Dold, Emanuel Sommer, Julius Kobialka +2Bayesian Loss Landscape
Deep Adaptive Dimension Reduction for Bayesian Inference in Inverse Problems
May 28, 2026Yueyang Wang, Xili Wang, Kejun Tang +3Inverse Problem Dimensionality Reduction
Attention as In-Context Empirical Bayes: A Two-Stage View via Particle Dynamics
May 28, 2026Matthew Smart, Soumya Ganguly, Nilava Metya +2In-Context Posterior
Enhancing Factuality through Consensus and Consistency in Summarization Using Minimum Bayes Risk Decoding
May 28, 2026Riza Setiawan Soetedjo, Yusuke Sakai, Hidetaka Kamigaito +3Summarization Facts
Thinned Mean Field Langevin Dynamics
May 27, 2026Zonghao Chen, Heishiro Kanagawa, François-Xavier Briol +2Mean-Field Limit Langevin Dynamics
Conservative neural posterior estimation via distributionally robust training
May 27, 2026William Laplante, Yuga Hikida, Charita Dellaporta +2Posterior Bayesian
Multi-Teacher Knowledge Distillation via Teacher-Informed Mixture Priors
May 27, 2026Luyang Fang, Yongkai Chen, Jiazhang Cai +2Multi-Teacher Distillation Knowledge Distillation
Why LLMs Fail at Causal Discovery and How Interventional Agents Escape
May 26, 2026Amartya Roy, Sonali ParbhooLarge Language Model Performance Finetuning
GenSBI: Generative Methods for Simulation-Based Inference in JAX
May 26, 2026Aurelio AmerioGenerative Processes Bayesian
Constrained Bayesian Experimental Design via Online Planning
May 26, 2026Yujia Guo, Daolang Huang, Xinyu Zhang +3Bayesian Experimental Design Constrained Optimization
Amortized Factor Inference Networks for Posterior Inference
May 26, 2026Joohwan Ko, Justin DomkePosterior Bayesian
A PAC-Bayesian View of Generalisation for Physics-Informed Machine Learning
May 25, 2026Thien V. Nguyen, Amaury Habrard, Benjamin GuedjPhysics-Informed Machine Learning Bayesian

Jun 11, 2026 · cond-mat.dis-nnJ/K move · Enter open · S save

A solvable model for unsupervised federated learning

Giovanni Catania, Aurélien Decelle, Gianluca Manzan, Beatriz Seoane+1

Institute for Cross-disciplinary Physics and Complex Systems IFISC (CSIC-UIB), Campus Universitat Illes Balears, 07122 Palma de Mallorca, Spain. · Escuela Técnica Superior de Ingenieros Industriales, Universidad Politécnica de Madrid, Calle de José Gutiérrez Abascal 2, Madrid 28006, Spain. · GISC - Grupo Interdisciplinar de Sistemas Complejos 28040 Madrid, Spain. · Inria Saclay - Tau team, Bât 660 Université Paris-Saclay, Orsay Cedex 91405 · LISN, Tau team, Bât 660 Université Paris-Saclay, Orsay Cedex 91405

We introduce a theoretical framework for analyzing federated learning in a generative setting through a teacher-multiple interacting students scenario, in which each student receives a distinct realization of the data, either through a different noise corruption or by accessing a different subset, possibly of varying size. Using theoretical tools in equilibrium disordered system, we analytically show that interactions among students systematically enhance learning performance: highly noisy students require fewer samples to recover the underlying pattern, while low-noise students achieve a larger overlap with the ground-truth signal. We derive the optimal Bayesian conditions for teacher recovery as functions of the sample complexity, noise level, and interaction strength, and validate these predictions through numerical simulations. The resulting dynamics can be mapped onto equilibrium sampling in a Restricted Boltzmann Machine with a structured hidden layer, providing a principled theoretical understanding of how interactions improve distributed generative modeling.

Federated Learning Distributional Learning Optimal Sample Complexity Bayesian Generative Models Theoretical Foundations

Open paper Ask about it PDF

Recent momentum

Neighbouring directions

Recent digests

17 new papers

5 new papers

7 new papers

Latest in Bayesian