87 citations · 222 across the 14 of their papers we have counts for
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cs.LG2020
Forecasting Hamiltonian dynamics without canonical coordinates
Anshul Choudhary, John F. Lindner, Elliott G. Holliday +3
Conventional neural networks are universal function approximators, but because they are unaware of underlying symmetries or physical laws, they may need impractically many training…
cs.NE2020★ 5 cited
Mastering high-dimensional dynamics with Hamiltonian neural networks
Scott T. Miller, John F. Lindner, Anshul Choudhary +2
We detail how incorporating physics into neural network design can significantly improve the learning and forecasting of dynamical systems, even nonlinear systems of many dimension…