Learning the Dynamics for Unknown Hyperbolic Conservation Laws Using Deep Neural Networks
Author:
Affiliation:
1. ExxonMobil Technology and Engineering Company, Spring, TX 77389 USA.
2. Department of Mathematics, Dartmouth College, Hanover, NH 03755 USA.
Funder
Multidisciplinary University Research Initiative
Air Force Office of Scientific Research
National Science Foundation
Publisher
Society for Industrial & Applied Mathematics (SIAM)
Reference35 articles.
1. A neural network based shock detection and localization approach for discontinuous Galerkin methods
2. On learning Hamiltonian systems from data
3. A data-driven physics-informed finite-volume scheme for nonclassical undercompressive shocks
4. Training with Noise is Equivalent to Tikhonov Regularization
5. Discovering governing equations from data by sparse identification of nonlinear dynamical systems
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