Recovering from Out-of-sample States via Inverse Dynamics in Offline Reinforcement Learning
–Neural Information Processing Systems
However, such pessimism for out-of-sample data could be too restricted and sample inefficient, as not all out-of-sample(unseen) states are not generalizable [20].
Neural Information Processing Systems
Feb-15-2026, 05:31:14 GMT
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