Bayesian Inference

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20 papers in the last four weeks, up 300% on the four weeks before. 0.2% of all new papers.

Jul 13Week of Sep 28

Latest papers 219

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ISBO: Scalable Spatio-Temporal Bayesian Optimization with Log Gaussian Cox Process Models via the INLA-SPDE Approach
Oct 8, 2026Kaichuang Yang, Håvard Rue, Jakob ZeitlerBayesian Optimization Bayesian Inference
KAUST · University of Oxford
Neural Decoding as Cognitive Inference
Oct 8, 2026Yi Guo, Changhong Jing, Yong Hu +4Neural Decoding Cognitive Modeling
Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China. · University of Chinese Academy Sciences, Beijing, China. · Department of Computing, The Hong Kong Polytechnic University, Hong Kong. +1
Scalable AI Uncertainty Quantification via Generalized Laplace Active Subspaces
Oct 8, 2026Wouter N. Edeling, Peter V. CoveneyUncertainty Quantification Uncertainty Calibration
Scientific Computing Group, CWI, Science park 123, Amsterdam, 1098XG, the Netherlands. · Faculty of Electrical Engineering, Mathematics and Computer Science, University of Twente, Hallenweg 15, Enschede, 7500AE, the Netherlands. · Centre for Computational Science, University College London, 20 Gordon Street, London, WC1H 0AJ, UK. +1
$σ$ Transfer: Uncertainty Transfer from Small to Large Networks under $μ\mathrm{P}$
Oct 8, 2026Richard Bergna, Fernando Ruiz Mazo, Nicolò Felicioni +2Uncertainty Quantification Bayesian Inference
University of Cambridge · Spotify
Feature Space Adaptation for Effortless Gaussian Process Flows
Oct 8, 2026Thomas Cowperthwaite, Louis Sharrock, Lachlan Astfalck +1Gaussian Processes Bayesian Inference
University of Cambridge · University College London · University of New South Wales +1
Shape-Bayes: Bayesian Inference of Structured Shapes under Visual Ambiguity
Oct 6, 2026Mani Kumar Tellamekala, Tosh Brown, Michel ValstarBayesian Inference Uncertainty Quantification
Amsterdam, The Netherlands · BlueSkeye AI · University of Nottingham, U.K.
ProximalFM: Amortized Proximal Causal Inference under Hidden Confounding
Oct 6, 2026Christophe Muller, Ayub Kharel, Alex Luedtke +6Amortized Inference Conditional Average Treatment Effect Estimation
University of Oxford · Harvard University · University of Illinois Urbana-Champaign +5
Generalized Matheron Variational Implicit Processes
Oct 6, 2026Luis A. Ortega, Andrés R. Masegosa, Thomas D. NielsenBayesian Inference Gaussian Processes
Aalborg University
Large Language Model Orchestration under Heterogeneous Preferences via Explicit Persona Inference
Oct 6, 2026Shuqing Shi, Ziyan Wang, Milind Tambe +1Multi-Agent Coordination Bayesian Inference
King’s College London, London, United Kingdom · Harvard University, Cambridge, MA, USA
Test-Time Adaptation of Reasoning Strategies with Bayesian Nonparametric Memory
Oct 5, 2026Keshav Ramji, Tahira Naseem, Ramón Fernandez AstudilloMemory-Augmented Language Models Bayesian Mixture Models
IBM Research AI
Bayesian Entropy-based Reordering for Calibrated Diffusion Language Models
Oct 4, 2026Zhejun Jiang, Mijung ParkConfidence Estimation in Language Models Bayesian Inference
The University of British Columbia
Posterior sampling by source-space MCMC via prior-based few-step transport maps
Oct 1, 2026Hoang Phuc Hau Luu, Marcelo Hartmann, Zhongjian WangMarkov Chain Monte Carlo Bayesian Inference
Division of Mathematical Sciences, School of Physical and Mathematical Sciences, Nanyang Technological University, Singapore. · Department of Computer Science, Faculty of Science, University of Helsinki, Finland.
Mitigating Representation Gaps in Amortized Bayesian Inference with Auxiliary Supervision
Sep 30, 2026Hans Olischläger, Svenja Jedhoff, Šimon Kucharský +3Simulation-Based Inference Amortized Inference
Department of Statistics, TU Dortmund University, Germany · Rensselaer Polytechnic Institute
QuanVI: Score-based Variational Inference via Quantum Maximally Mixed States
Sep 30, 2026Yuchen Cong, Zerui Tao, Chao Li +2Bayesian Inference Quantum-Inspired ML
Juntendo University · RIKEN-AIP
Amortized Data Borrowing with Exchangeability-Aware Neural Posterior Estimation
Sep 30, 2026Chin-Hung Huang, JooChul Lee, Huan HeNeural Posterior Estimation Amortized Inference
Department of Mathematics and Statistics Auburn University
Principled MAP estimation for inverse problems: bridging the gap between convergence and performance
Sep 29, 2026Alexandre Lagier, Valentine Tosel, Anne Gagneux +2Bayesian Inverse Problems Bayesian Inference
ENS de Lyon, CNRS, Université Claude Bernard Lyon 1, Inria, LIP UMR 5668, 69342 Lyon Cedex 07, France · Univ. Bordeaux, Inria, Bordeaux INP, IMB, UMR 5251, F-33400 Talence, France · Inria, ENS de Lyon, CNRS, Université Claude Bernard Lyon 1, LIP UMR 5668, 69342 Lyon Cedex 07, France
Small transformers track Bayesian evidence for latent common causes via a context-invariant mechanism
Sep 28, 2026Amir Mohammadpour, Michael FrankeBayesian Inference Causal Reasoning in Language Models
Department of Linguistics, University of Tübingen
Singularities of Non-negative Matrix Factorization and their application to Bayesian inference
Sep 28, 2026Naoki Hayashi, Yota Maeda, Yasushi EsakiNon-Negative Matrix Factorization Low-Rank Matrix Decomposition
Toyota Central R&D Labs., Inc.
Is your uncertainty map wrong, or is its target? Exact diagnostics for the Tweedie diagonal, and a gradient-free alternative
Sep 27, 2026Vicent Ribas, Anna Oliveras TousUncertainty Quantification Bayesian Inference
Eurecat · University of Barcelona
Direct Message Approximation (DMA): A Consistency-Based Framework for Tractable Approximate Inference on Factor Graphs
Sep 24, 2026Ralf Herbrich, Rainer Schlosser, Jan Lemcke +11Efficient Inference Uncertainty Quantification
Hasso Plattner Institute University of Potsdam Potsdam, Germany
Prior-Amortized In-Context Bayesian Inference for Generalized Linear Mixed-Effects Models
Sep 21, 2026Alex Kipnis, Marcel Binz, Eric SchulzNeural Posterior Estimation Amortized Inference
Institute for Human-Centered AI, Helmholtz Munich, Germany
TAP Accuracy Below the Fluctuation Scale and Universal Posterior Geometry in Spherical Linear Models
Sep 17, 2026Jingbo Liu, Zhiyuan YuBayesian Inference
Department of Statistics University of Illinois Urbana-Champaign Champaign, IL 61820
Compressed Active Subspaces for Scalable Bayesian Inference
Sep 17, 2026Thomas Flynn, Sanket Jantre, Byung-Jun Yoon +1Uncertainty Quantification Bayesian Inference
Computing and Data Sciences Directorate, Brookhaven National Laboratory, Upton, NY, USA · Department of Electrical & Computer Engineering, Texas A&M University, College Station, TX, USA · Mathematics and Computer Science Division, Argonne National Laboratory, Lemont, IL, USA
Quenched Ensemble Sampling
Sep 14, 2026David YallupBayesian Inference Posterior Sampling
Kavli Institute for Cosmology Cambridge Institute of Astronomy, University of Cambridge, Madingley Road, Cambridge, CB3 0HA, UK
Predictive Likelihood Ratios for Language Model Watermark Detection
Sep 14, 2026Li MaBayesian Inference LLM Watermarking
Department of Statistics and Data Science Institute, University of Chicago
Bio-inspired Learning and Decision-Making with Probabilistic In-Memory Computing Hardware: Part 1
Sep 12, 2026Thomas Dalgaty, Eiji Kawasaki, Miguel de Prado +2Compute-in-Memory Bayesian Inference
CEA-List, Grenoble, France
When Agents Disagree: Bayesian Backward Reasoning as a Label-Free Anchor for Multi-Agent Collective Decision-Making
Sep 12, 2026Ken Chen, Wei Wang, Sachith Seneviratne +2Multi-Agent LLM Systems Bayesian Inference
Department of Mechanical Engineering, The University of Melbourne, Melbourne, Australia · Department of Mechanical Engineering, Sri Lanka Institute of Information Technology, Sri Lanka
A Generalization of Amari's Bayesian Duality
Sep 8, 2026Mohammad Emtiyaz Khan, Thomas MöllenhoffInformation Geometry Bayesian Inference
RIKEN Center for Advanced Intelligence Project, 1-4-1 Nihonbashi, Chuo-ku, Tokyo, 103-0027, Tokyo, Japan. · Department of Computer Science, Technische Universität Darmstadt, Hochschulstraße 10, Darmstadt, 64289, Hessen, Germany. · The Hessian Center for Artificial Intelligence, Landwehrstraße 50a, Darmstadt, 64293, Hessen, Germany.
Bayesian Matrix-Valued Graphs for Context-Dependent Multivariate Relationships
Sep 7, 2026Papri DeyGraph Structure Learning Bayesian Inference
Thermodynamic Cyclic Processes with Markov Samplers in Bayesian Inference
Sep 7, 2026Heinrich von Campe, Bjoern Malte SchaeferMarkov Chain Monte Carlo Bayesian Inference
Interdisziplinäres Zentrum für wissenschaftliches Rechnen, Universität Heidelberg · Tübingen AI Center, University of Tübingen · ELLIS Institute Tübingen +2

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ISBO: Scalable Spatio-Temporal Bayesian Optimization with Log Gaussian Cox Process Models via the INLA-SPDE Approach

Kaichuang Yang, Håvard Rue, Jakob Zeitler

KAUST · University of Oxford

Bayesian Optimization Bayesian Inference Gaussian Processes

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Bayesian Optimization (BO) is a popular method for efficiently optimizing expensive black-box objectives. However, BO utilizing standard Gaussian Processes is ill-suited for doubly stochastic Cox Processes that are often used in spatio-temporal problem spaces. We introduce INLA-SPDE Spatio-Temporal Bayesian Optimization (ISBO): the first scalable BO framework for spatio-temporal data, that models the log-intensity with a Log-Gaussian Cox Process(LGCP) and performs inference via Integrated Nested Laplace Approximation and Stochastic Partial Differential Equations (INLA-SPDE) approach. Using a Matern field on meshes yields a sparse Gaussian Markov Random Field, where INLA provides fast and accurate posterior inference throughout sequential optimization. ISBO stably locates high-intensity regions and the peak of the latent intensity with minimal evaluations. A time-varying Upper Confidence Bound acquisition with masking avoids revisits, while penalized-complexity priors regularize early rounds. Experiments on synthetic and real-world spatio-temporal datasets show accurate peak discovery, intensity recovery, and substantial speedups over an RKHS-based baseline, positioning ISBO as a practical choice for BO with point-process data.

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Latest papers 219