42 citations · 42 across the 2 of their papers we have counts for
2 papers
cs.LG2025
Learning Generalized Hamiltonian Dynamics with Stability from Noisy Trajectory Data
Luke McLennan, Yi Wang, Ryan Farell +2
We introduce a robust framework for learning various generalized Hamiltonian dynamics from noisy, sparse phase-space data and in an unsupervised manner based on variational Bayesia…
cs.LG2021★ 42 cited
Recipes for when Physics Fails: Recovering Robust Learning of Physics Informed Neural Networks
Chandrajit Bajaj, Luke McLennan, Timothy Andeen +1
Physics-informed Neural Networks (PINNs) have been shown to be effective in solving partial differential equations by capturing the physics induced constraints as a part of the tra…