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cs.LG2025
Improving ideal MHD equilibrium accuracy with physics-informed neural networks
Timo Thun, Andrea Merlo, Rory Conlin +2
We present a novel approach to compute three-dimensional Magnetohydrodynamic equilibria by parametrizing Fourier modes with artificial neural networks and compare it to equilibria…
cs.LG2022
Exploration via Planning for Information about the Optimal Trajectory
Viraj Mehta, Ian Char, Joseph Abbate +5
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…