3 papers
Physics-informed neural networks to solve inverse problems in unbounded domains
Gregorio Pérez-Bernal, Oscar Rincón-Cardeño, Silvana Montoya-Noguera +1
Inverse problems are extensively studied in applied mathematics, with applications ranging from acoustic tomography for medical diagnosis to geophysical exploration. Physics inform…
Benchmarking Physics-Informed Neural Networks and Boundary Elements Methods for Wave Scattering
Oscar Rincón-Cardeno, Gregorio Pérez Bernal, Silvana Montoya Noguera +1
This study compares the Boundary Element Method (BEM) and Physics-Informed Neural Networks (PINNs) for solving the two-dimensional Helmholtz equation in wave scattering problems. T…
Decoding street network morphologies and their correlation to travel mode choice
Juan Fernando Riascos-Goyes, Michael Lowry, Nicolás Guarín-Zapata +1
Urban morphology has long been recognized as a factor shaping human mobility, yet comparative and formal classifications of urban form across metropolitan areas remain limited. Bui…