3 citations · 3 across the 2 of their papers we have counts for
2 papers
math.NA2026
Pointwise Error Estimates for Numerical Physics-Informed Neural Networks
Nivar Anwer, Marien Chenaud, José Alves +1
Physics-informed neural networks are often evaluated by residual losses sampled at finitely many points, which do not by themselves certify pointwise values of a partial differenti…
cs.LG2023★ 3 cited
Physics-Informed Graph Convolutional Networks: Towards a generalized framework for complex geometries
Marien Chenaud, José Alves, Frédéric Magoulès
Since the seminal work of [9] and their Physics-Informed neural networks (PINNs), many efforts have been conducted towards solving partial differential equations (PDEs) with Deep L…