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Chenyuan Hu

2 accepted papers

2025

A Forget-and-Grow Strategy for Deep Reinforcement Learning Scaling in Continuous Control

ICML 2025poster

Deep reinforcement learning for continuous control has recently achieved impressive progress. However, existing methods often suffer from primacy bias—a tendency to overfit early experiences stored in the replay buffer—which limits an RL agent’s sample efficiency and generalizability. A common exist…

Cited by 0SourcePDFScholar
2024

3D Diffusion Policy: Generalizable Visuomotor Policy Learning via Simple 3D Representations

RSS 2024poster

Imitation learning provides an efficient way to teach robots dexterous skills; however, learning complex skills robustly and generalizablely usually consumes large amounts of human demonstrations. To tackle this challenging problem, we present 3D Diffusion Policy (DP3), a novel visual imitation lear…