Výsledky vyhledávání - "Boyer, Mark D"

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Exploration via Planning for Information about the Optimal Trajectory

Autor: Mehta, Viraj, Char, Ian, Abbate, Joseph, Conlin, Rory, Boyer, Mark D., Ermon, Stefano, Schneider, Jeff, Neiswanger, Willie

Many potential applications of reinforcement learning (RL) are stymied by the large numbers of samples required to learn an effective policy. This is especially true when applying RL to real-world control tasks, e.g. in the sciences or robotics, wher

Externí odkaz: http://arxiv.org/abs/2210.04642

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Neural Dynamical Systems: Balancing Structure and Flexibility in Physical Prediction

Autor: Mehta, Viraj, Char, Ian, Neiswanger, Willie, Chung, Youngseog, Nelson, Andrew Oakleigh, Boyer, Mark D, Kolemen, Egemen, Schneider, Jeff

We introduce Neural Dynamical Systems (NDS), a method of learning dynamical models in various gray-box settings which incorporates prior knowledge in the form of systems of ordinary differential equations. NDS uses neural networks to estimate free pa

Externí odkaz: http://arxiv.org/abs/2006.12682

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Offline Contextual Bayesian Optimization for Nuclear Fusion

Autor: Chung, Youngseog, Char, Ian, Neiswanger, Willie, Kandasamy, Kirthevasan, Nelson, Andrew Oakleigh, Boyer, Mark D, Kolemen, Egemen, Schneider, Jeff

Nuclear fusion is regarded as the energy of the future since it presents the possibility of unlimited clean energy. One obstacle in utilizing fusion as a feasible energy source is the stability of the reaction. Ideally, one would have a controller fo

Externí odkaz: http://arxiv.org/abs/2001.01793

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