2 papers
physics.comp-ph2026
A Scoping Review of Physics Informed Machine Learning for Wave Propagation Modeling in Seismology
Óscar Rincón-Cardeño, Gregorio Pérez-Bernal, Silvana Montoya-Noguera +1
Standard numerical methods accurately simulate seismic waves but are computationally expensive, particularly for inverse problems. Some machine-learning-based alternatives have eme…
cs.LG2025
Evaluation of Sampling Strategies and Physics-Informed Kolmogorov--Arnold Networks in Unbounded Domains
Gregorio Pérez-Bernal, Oscar Rincón-Cardeño, Silvana Montoya-Noguera +1
Physics-informed neural networks (PINNs) have emerged as an effective approach for solving partial differential equations (PDEs) by incorporating physical laws into the learning pr…