Diverse Policies Recovering via Pointwise Mutual Information Weighted Imitation Learning

This work focuses on recovering stylistically diverse policies from expert trajectories by weighting state-action pairs with pointwise mutual information.

Recommended citation: Yang, H.*, Yao, J.*, Liu, W., et al. (2025). "Diverse Policies Recovering via Pointwise Mutual Information Weighted Imitation Learning." ICLR 2025.
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