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Bayesian Inference

1724 directly classified papers

Papers per year

Papers

Progressive Bayesian Inference for Scribble-Supervised Semantic Segmentation AAAI 2023
Tangentially Elongated Gaussian Belief Propagation for Event-Based Incremental Optical Flow Estimation CVPR 2023
BANSAC: A Dynamic BAyesian Network for Adaptive SAmple Consensus ICCV 2023
Distance-to-Set Priors and Constrained Bayesian Inference AISTATS 2023
Posterior Coreset Construction with Kernelized Stein Discrepancy for Model-Based Reinforcement Learning AAAI 2023
Self-Interpretable Time Series Prediction with Counterfactual Explanations ICML 2023
Bayesian Design Principles for Frequentist Sequential Learning ICML 2023
Bayesian Estimation of Differential Privacy ICML 2023
Semiparametrically Efficient Off-Policy Evaluation in Linear Markov Decision Processes ICML 2023
Towards Coherent Image Inpainting Using Denoising Diffusion Implicit Models ICML 2023
Bayesian Federated Neural Matching That Completes Full Information AAAI 2023
PAC-Bayesian Offline Contextual Bandits With Guarantees ICML 2023
Bayesian Calibration of Imperfect Computer Models using Physics-Informed Priors JMLR 2023
Posterior Consistency for Bayesian Relevance Vector Machines JMLR 2023
Meta-Uncertainty in Bayesian Model Comparison AISTATS 2023
Prior Specification for Bayesian Matrix Factorization via Prior Predictive Matching JMLR 2023
Posterior Contraction for Deep Gaussian Process Priors JMLR 2023
BNN-DP: Robustness Certification of Bayesian Neural Networks via Dynamic Programming ICML 2023
The neural dynamics of word recognition and integration EMNLP 2023
Evidential Conditional Neural Processes AAAI 2023
Sensing Cox Processes via Posterior Sampling and Positive Bases AISTATS 2022
A Predictive Approach to Bayesian Nonparametric Survival Analysis AISTATS 2022
Interpreting Time-Varying Dynamic Bayesian Networks for Earth Climate Modelling PGM 2022
Lifted Division for Lifted Hugin Belief Propagation AISTATS 2022
Thompson Sampling with a Mixture Prior AISTATS 2022