posterior sampling

Efficient Exploration in Average-Reward Constrained Reinforcement Learning: Achieving Near-Optimal Regret With Posterior Sampling ICML 2024 Enhancing Transfer Learning with Flexible Nonparametric Posterior Sampling ICLR 2024 Entropy-MCMC: Sampling from Flat Basins with Ease ICLR 2024 EVaDE : Event-Based Variational Thompson Sampling for Model-Based Reinforcement Learning ACML 2024 Exploiting Causal Graph Priors with Posterior Sampling for Reinforcement Learning ICLR 2024 Fair Active Learning in Low-Data Regimes UAI 2024 Fast Value Tracking for Deep Reinforcement Learning ICLR 2024 From Posterior Sampling to Meaningful Diversity in Image Restoration ICLR 2024 Image Inpainting via Tractable Steering of Diffusion Models ICLR 2024 Improving Diffusion-Based Image Restoration with Error Contraction and Error Correction AAAI 2024 Label Shift Estimation for Class-Imbalance Problem: A Bayesian Approach WACV 2024 Learning Diffusion Priors from Observations by Expectation Maximization NeurIPS 2024 Learning with Posterior Sampling for Revenue Management under Time-varying Demand IJCAI 2024 MDFL: Multi-Domain Diffusion-Driven Feature Learning AAAI 2024 Meta-Reinforcement Learning Robust to Distributional Shift Via Performing Lifelong In-Context Learning ICML 2024 Model-based Policy Optimization under Approximate Bayesian Inference AISTATS 2024 Molecule Design by Latent Prompt Transformer NeurIPS 2024 On Estimating the Gradient of the Expected Information Gain in Bayesian Experimental Design AAAI 2024 Online Posterior Sampling with a Diffusion Prior NeurIPS 2024 Optimal Exploration is no harder than Thompson Sampling AISTATS 2024 pcaGAN: Improving Posterior-Sampling cGANs via Principal Component Regularization NeurIPS 2024 Plug-and-Play Posterior Sampling under Mismatched Measurement and Prior Models ICLR 2024 Posterior Sampling Based on Gradient Flows of the MMD with Negative Distance Kernel ICLR 2024 Practical Bayesian Algorithm Execution via Posterior Sampling NeurIPS 2024 Principled Probabilistic Imaging using Diffusion Models as Plug-and-Play Priors NeurIPS 2024