5 citations · 5 across the 1 of their papers we have counts for
3 papers
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…
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…
Suppression and Revival of Oscillations through Time-varying Interaction
Sudhanshu Shekhar Chaurasia, Anshul Choudhary, Manish Dev Shrimali +1
We explore the dynamical consequences of switching the coupling form in a system of coupled oscillators. We consider two types of switching, one where the coupling function changes…