2 papers
physics.comp-ph2025
Physics-Informed Neural Networks with Dynamical Boundary Constraints
Andrés MartÃnez-Esteban, Pablo Calvo-Barlés, Luis MartÃn-Moreno +1
Physics-informed neural networks (PINNs) are numerical solvers that embed all the physical information of a system into the loss function of a neural network. In this way the learn…
physics.comp-ph2025
Learning finite symmetry groups of dynamical systems via equivariance detection
Pablo Calvo-Barlés, Sergio G. Rodrigo, Luis MartÃn-Moreno
In this work, we introduce the Equivariance Seeker Model (ESM), a data-driven method for discovering the underlying finite equivariant symmetry group of an arbitrary function. ESM…