12 citations · 12 across the 1 of their papers we have counts for
3 papers
physics.flu-dyn2025
An approximate Riemann solver approach in Physics-Informed Neural Networks for hyperbolic conservation laws
Jorge F. Urbán, José A. Pons
This study enhances the application of Physics-Informed Neural Networks (PINNs) for modeling discontinuous solutions in both hydrodynamics and relativistic hydrodynamics. Conventio…
physics.comp-ph2024
Unveiling the optimization process of Physics Informed Neural Networks: How accurate and competitive can PINNs be?
Jorge F. Urbán, Petros Stefanou, José A. Pons
This study investigates the potential accuracy boundaries of physics-informed neural networks, contrasting their approach with previous similar works and traditional numerical meth…
astro-ph.HE2023★ 12 cited
Solving the Pulsar Equation using Physics-Informed Neural Networks
Petros Stefanou, Jorge F. Urbán, José A. Pons
In this study, Physics-Informed Neural Networks (PINNs) are skilfully applied to explore a diverse range of pulsar magneto-spheric models, specifically focusing on axisymmetric cas…