posterior sampling

Langevin Monte Carlo for Contextual Bandits ICML 2022 Model-based Meta Reinforcement Learning using Graph Structured Surrogate Models and Amortized Policy Search ICML 2022 Model-based RL with Optimistic Posterior Sampling: Structural Conditions and Sample Complexity NeurIPS 2022 Non-Linear Reinforcement Learning in Large Action Spaces: Structural Conditions and Sample-efficiency of Posterior Sampling COLT 2022 Online Learning for Unknown Partially Observable MDPs AISTATS 2022 Optimistic Posterior Sampling for Reinforcement Learning with Few Samples and Tight Guarantees NeurIPS 2022 Pathfinder: Parallel quasi-Newton variational inference JMLR 2022 POEM: Out-of-Distribution Detection with Posterior Sampling ICML 2022 Score-Guided Intermediate Level Optimization: Fast Langevin Mixing for Inverse Problems ICML 2022 Score Matched Neural Exponential Families for Likelihood-Free Inference JMLR 2022 Sensing Cox Processes via Posterior Sampling and Positive Bases AISTATS 2022 Stochastic Deep Networks with Linear Competing Units for Model-Agnostic Meta-Learning ICML 2022 Wide Bayesian neural networks have a simple weight posterior: theory and accelerated sampling ICML 2022 A Provably Efficient Model-Free Posterior Sampling Method for Episodic Reinforcement Learning NeurIPS 2021 Black-box density function estimation using recursive partitioning ICML 2021 Fairness for Image Generation with Uncertain Sensitive Attributes ICML 2021 Federated stochastic gradient Langevin dynamics UAI 2021 HINT: Hierarchical Invertible Neural Transport for Density Estimation and Bayesian Inference AAAI 2021 Infinite Time Horizon Safety of Bayesian Neural Networks NeurIPS 2021 Information Directed Sampling for Sparse Linear Bandits NeurIPS 2021 Instance-Optimal Compressed Sensing via Posterior Sampling ICML 2021 Model-based Reinforcement Learning for Continuous Control with Posterior Sampling ICML 2021 Pathwise Conditioning of Gaussian Processes JMLR 2021 Robust Compressed Sensing MRI with Deep Generative Priors NeurIPS 2021 SNIPS: Solving Noisy Inverse Problems Stochastically NeurIPS 2021