bayesian inference

1904 papers

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Also known as

MCMC MBR BI BVMM MAP

Co-occurring keywords

variational inference (2069) markov chain monte carlo (724) gaussian process (1198) probabilistic modeling (851) uncertainty quantification (1365) posterior distribution (259) bayesian learning (185) gibbs sampling (201) graphical model (863) probabilistic model (476)

Papers

Reasoning over Uncertain Text by Generative Large Language Models AAAI 2025

Improving Diffusion Inverse Problem Solving with Decoupled Noise Annealing CVPR 2025

Unified Uncertainty-Aware Diffusion for Multi-Agent Trajectory Modeling CVPR 2025

Bayesian Test-Time Adaptation for Vision-Language Models CVPR 2025

How good is your Laplace approximation of the Bayesian posterior? Finite-sample computable error bounds for a variety of useful divergences JMLR 2025

Statistical field theory for Markov decision processes under uncertainty JMLR 2025

Bayesian Sparse Gaussian Mixture Model for Clustering in High Dimensions JMLR 2025

Fine-Grained Change Point Detection for Topic Modeling with Pitman-Yor Process JMLR 2025

Copula-based Sensitivity Analysis for Multi-Treatment Causal Inference with Unobserved Confounding JMLR 2025

Derivative-Informed Neural Operator Acceleration of Geometric MCMC for Infinite-Dimensional Bayesian Inverse Problems JMLR 2025

Integrating Inference and Experimental Design for Contextual Behavioral Model Learning AAAI 2025

Partially Blinded Unlearning: Class Unlearning for Deep Networks from Bayesian Perspective AAAI 2025

Modelling Populations of Interaction Networks via Distance Metrics JMLR 2025

Few-Shot Open-Set Classification via Reasoning-Aware Decomposition EMNLP 2025

Optimizing Heat Alert Issuance with Reinforcement Learning AAAI 2025

Low-Entropy Watermark Detection via Bayes’ Rule Derived Detector ACL 2025

Cache-Efficient Posterior Sampling for Reinforcement Learning with LLM-Derived Priors Across Discrete and Continuous Domains EMNLP 2025

REALM: Recursive Relevance Modeling for LLM-based Document Re-Ranking EMNLP 2025

Combining Priors with Experience: Confidence Calibration Based on Binomial Process Modeling AAAI 2025

Approximate Bilevel Difference Convex Programming for Bayesian Risk Markov Decision Processes AAAI 2025

Feature Learning in Finite-Width Bayesian Deep Linear Networks with Multiple Outputs and Convolutional Layers JMLR 2025

Conditional Wasserstein Distances with Applications in Bayesian OT Flow Matching JMLR 2025

Bayesian Multi-Group Gaussian Process Models for Heterogeneous Group-Structured Data JMLR 2025

Bayes Meets Bernstein at the Meta Level: an Analysis of Fast Rates in Meta-Learning with PAC-Bayes JMLR 2025

Bayesian Score Calibration for Approximate Models JMLR 2025