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Found 2 papers, 1 papers with code
Offline Reinforcement Learning with Behavioral Supervisor Tuning
Offline reinforcement learning (RL) algorithms are applied to learn performant, well-generalizing policies when provided with a static dataset of interactions.
Time-series Transformer Generative Adversarial Networks
We consider limitations posed specifically on time-series data and present a model that can generate synthetic time-series which can be used in place of real data.
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