most citedSuccessive Model-Agnostic Meta-Learning for Few-Shot Fault Time Series Prognosis

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cs.LG2026

Maximum Entropy Behavior Exploration for Sim2Real Zero-Shot Reinforcement Learning

Jiajun Hu, Nuria Armengol Urpi, Jin Cheng +1

Zero-shot reinforcement learning (RL) algorithms aim to learn a family of policies from a reward-free dataset, and recover optimal policies for any reward function directly at test…

cs.LG2023★ 1 cited

Successive Model-Agnostic Meta-Learning for Few-Shot Fault Time Series Prognosis

Hai Su, Jiajun Hu, Songsen Yu

Meta learning is a promising technique for solving few-shot fault prediction problems, which have attracted the attention of many researchers in recent years. Existing meta-learnin…