Symplectic Momentum Neural Networks - Using Discrete Variational Mechanics as a prior in Deep Learning. (arXiv:2201.08281v1 [cs.LG])

With deep learning being gaining attention from the research community for
prediction and control of real physical systems, learning important
representations is becoming now more than ever mandatory. It is of extremely
importance that deep learning representations are coherent with physics. When
learning from discrete data this can be guaranteed by including some sort of
prior into the learning, however not all discretization priors preserve
important structures from the physics. In this paper we introduce Symplectic
Momentum Neural Networks (SyMo) …

arxiv deep learning learning networks neural networks prior