Bayesian Inference

Bayesian Optimistic Optimization: Optimistic Exploration for Model-based Reinforcement Learning NeurIPS 2022 Bayesian Optimization for Distributionally Robust Chance-constrained Problem ICML 2022 Bayesian Optimization over Discrete and Mixed Spaces via Probabilistic Reparameterization NeurIPS 2022 Bayesian Optimization over Permutation Spaces AAAI 2022 Bayesian Persuasion for Algorithmic Recourse NeurIPS 2022 Bayesian Phylogenetic Cognate Prediction NAACL 2022 Bayesian Pseudo Posterior Mechanism under Asymptotic Differential Privacy JMLR 2022 Bayesian quantile and expectile optimisation UAI 2022 Bayesian Recurrent Units and the Forward-Backward Algorithm Interspeech 2022 Bayesian Reinforcement Learning for Single-Episode Missions in Partially Unknown Environments CoRL 2022 Bayesian Risk Markov Decision Processes NeurIPS 2022 Bayesian spillover graphs for dynamic networks UAI 2022 Bayesian Spline Learning for Equation Discovery of Nonlinear Dynamics with Quantified Uncertainty NeurIPS 2022 Bayesian subset selection and variable importance for interpretable prediction and classification JMLR 2022 Bayesian Transformer Using Disentangled Mask Attention Interspeech 2022 Bayesian Uncertainty and Expected Gradient Length - Regression: Two Sides of the Same Coin? WACV 2022 Being a Bit Frequentist Improves Bayesian Neural Networks AISTATS 2022 Bias aware probabilistic Boolean matrix factorization UAI 2022 Black-box coreset variational inference NeurIPS 2022 Bounding the Error of Discretized Langevin Algorithms for Non-Strongly Log-Concave Targets JMLR 2022 Bregman Proximal Langevin Monte Carlo via Bregman-Moreau Envelopes ICML 2022 Calibrated and Sharp Uncertainties in Deep Learning via Density Estimation ICML 2022 Calibrating Factual Knowledge in Pretrained Language Models EMNLP 2022 Calibrating Zero-shot Cross-lingual (Un-)structured Predictions EMNLP 2022 CATVI: Conditional and Adaptively Truncated Variational Inference for Hierarchical Bayesian Nonparametric Models AISTATS 2022