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stat.ML2026
Learning Upper Lower Value Envelopes to Shape Online RL: A Principled Approach
Sebastian Reboul, Hélène Halconruy
We investigate the fundamental problem of leveraging offline data to accelerate online reinforcement learning - a direction with strong potential but limited theoretical grounding.…
stat.ML2024
Variational Diffusion Posterior Sampling with Midpoint Guidance
Badr Moufad, Yazid Janati, Lisa Bedin +4
Diffusion models have recently shown considerable potential in solving Bayesian inverse problems when used as priors. However, sampling from the resulting denoising posterior distr…