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Found 2 papers, 2 papers with code
Actively Learning Costly Reward Functions for Reinforcement Learning
Transfer of recent advances in deep reinforcement learning to real-world applications is hindered by high data demands and thus low efficiency and scalability.
Machine learning for rapid discovery of laminar flow channel wall modifications that enhance heat transfer
Numerical simulation of fluids plays an essential role in modeling many physical phenomena, which enables technological advancements, contributes to sustainable practices, and expands our understanding of various natural and engineered systems.
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