ICML "posterior sampling" Papers
10 papers found
Diffusion Posterior Sampling is Computationally Intractable
Shivam Gupta, Ajil Jalal, Aditya Parulekar et al.
ICML 2024posterarXiv:2402.12727
Efficient Exploration in Average-Reward Constrained Reinforcement Learning: Achieving Near-Optimal Regret With Posterior Sampling
Danil Provodin, Maurits Kaptein, Mykola Pechenizkiy
ICML 2024posterarXiv:2405.19017
Embarrassingly Parallel GFlowNets
Tiago Silva, Luiz Carvalho, Amauri Souza et al.
ICML 2024posterarXiv:2406.03288
Feel-Good Thompson Sampling for Contextual Dueling Bandits
Xuheng Li, Heyang Zhao, Quanquan Gu
ICML 2024posterarXiv:2404.06013
Listening to the noise: Blind Denoising with Gibbs Diffusion
David Heurtel-Depeiges, Charles Margossian, Ruben Ohana et al.
ICML 2024posterarXiv:2402.19455
Meta-Reinforcement Learning Robust to Distributional Shift Via Performing Lifelong In-Context Learning
TengYe Xu, Zihao Li, Qinyuan Ren
ICML 2024poster
Posterior Sampling-Based Bayesian Optimization with Tighter Bayesian Regret Bounds
Shion Takeno, Yu Inatsu, Masayuki Karasuyama et al.
ICML 2024posterarXiv:2311.03760
Q-Star Meets Scalable Posterior Sampling: Bridging Theory and Practice via HyperAgent
Yingru Li, Jiawei Xu, Lei Han et al.
ICML 2024posterarXiv:2402.10228
Stochastic Localization via Iterative Posterior Sampling
Louis Grenioux, Maxence Noble, Marylou Gabrié et al.
ICML 2024spotlightarXiv:2402.10758
The Perception-Robustness Tradeoff in Deterministic Image Restoration
Guy Ohayon, Tomer Michaeli, Michael Elad
ICML 2024spotlightarXiv:2311.09253