bayesian inference

On the Robustness to Misspecification of α-posteriors and Their Variational Approximations JMLR 2022 On the Value of Prior in Online Learning to Rank AISTATS 2022 Optimal Scaling for Locally Balanced Proposals in Discrete Spaces NeurIPS 2022 Optimistic Posterior Sampling for Reinforcement Learning with Few Samples and Tight Guarantees NeurIPS 2022 PACm-Bayes: Narrowing the Empirical Risk Gap in the Misspecified Bayesian Regime AISTATS 2022 Parallel MCMC Without Embarrassing Failures AISTATS 2022 Parallel Tempering With a Variational Reference NeurIPS 2022 Parameterized Completeness Results for Bayesian Inference PGM 2022 Personalized Federated Learning via Variational Bayesian Inference ICML 2022 Phase transitions in when feedback is useful NeurIPS 2022 Pick-and-Mix Information Operators for Probabilistic ODE Solvers AISTATS 2022 Posterior and Computational Uncertainty in Gaussian Processes NeurIPS 2022 Predictive State Propensity Subclassification (PSPS): A causal inference algorithm for data-driven propensity score stratification CLeaR 2022 Pre-Train Your Loss: Easy Bayesian Transfer Learning with Informative Priors NeurIPS 2022 Probabilistic Fusion of Neural Networks that Incorporates Global Information ACML 2022 Probabilistic Numerical Method of Lines for Time-Dependent Partial Differential Equations AISTATS 2022 Probabilistic ODE Solutions in Millions of Dimensions ICML 2022 Projection Predictive Inference for Generalized Linear and Additive Multilevel Models AISTATS 2022 Public Signaling in Bayesian Ad Auctions IJCAI 2022 QLSD: Quantised Langevin Stochastic Dynamics for Bayesian Federated Learning AISTATS 2022 Random Effect Bandits AISTATS 2022 Rapidly Mixing Multiple-try Metropolis Algorithms for Model Selection Problems NeurIPS 2022 Rethinking Variational Inference for Probabilistic Programs with Stochastic Support NeurIPS 2022 RL with KL penalties is better viewed as Bayesian inference EMNLP 2022 Robust Anytime Learning of Markov Decision Processes NeurIPS 2022