Corpus ID: 225067856

Simplifying Hamiltonian and Lagrangian Neural Networks via Explicit Constraints

@article{Finzi2020SimplifyingHA,
  title={Simplifying Hamiltonian and Lagrangian Neural Networks via Explicit Constraints},
  author={Marc Finzi and K. Wang and A. Wilson},
  journal={ArXiv},
  year={2020},
  volume={abs/2010.13581}
}

Marc Finzi, K. Wang, A. Wilson

Published 2020

Computer Science, Mathematics, Physics

ArXiv

Reasoning about the physical world requires models that are endowed with the right inductive biases to learn the underlying dynamics. Recent works improve generalization for predicting trajectories by learning the Hamiltonian or Lagrangian of a system rather than the differential equations directly. While these methods encode the constraints of the systems using generalized coordinates, we show that embedding the system into Cartesian coordinates and enforcing the constraints explicitly with… CONTINUE READING

View PDF on arXiv

Save to Library

Create Alert

Cite

Launch Research Feed