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

Optimizing Heat Alert Issuance with Reinforcement Learning AAAI 2025

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

Frequency-Guided Posterior Sampling for Diffusion-Based Image Restoration ICCV 2025

Explicit Bayesian Inference to Uncover the Latent Themes of Large Language Models ACL 2025

K-Sort Arena: Efficient and Reliable Benchmarking for Generative Models via K-wise Human Preferences CVPR 2025

Bayesian Score Calibration for Approximate Models JMLR 2025

On Consistent Bayesian Inference from Synthetic Data JMLR 2025

Enough Coin Flips Can Make LLMs Act Bayesian ACL 2025

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

Theorem-of-Thought: A Multi-Agent Framework for Abductive, Deductive, and Inductive Reasoning in Language Models ACL 2025

Language-Informed Synthesis of Rational Agent Models for Grounded Theory-of-Mind Reasoning On-the-fly EMNLP 2025

Probabilistic size-and-shape functional mixed models NIPS 2024

Tensor-train methods for sequential state and parameter learning in state-space models JMLR 2024

Empowering Active Learning for 3D Molecular Graphs with Geometric Graph Isomorphism NIPS 2024

Bayesian Differentiable Physics for Cloth Digitalization CVPR 2024

Measuring Sample Quality in Algorithms for Intractable Normalizing Function Problems JMLR 2024

Preferential Normalizing Flows NIPS 2024

Gated Inference Network: Inference and Learning State-Space Models NIPS 2024

Variational Multi-scale Representation for Estimating Uncertainty in 3D Gaussian Splatting NIPS 2024

Data-Adaptive Probabilistic Likelihood Approximation for Ordinary Differential Equations AISTATS 2024

Nonasymptotic analysis of Stochastic Gradient Hamiltonian Monte Carlo under local conditions for nonconvex optimization JMLR 2024

Bias Detection via Signaling NIPS 2024

Evidence Estimation in Gaussian Graphical Models Using a Telescoping Block Decomposition of the Precision Matrix JMLR 2024

Bayesian Adaptive Calibration and Optimal Design NIPS 2024

Thompson Sampling For Combinatorial Bandits: Polynomial Regret and Mismatched Sampling Paradox NIPS 2024