no code implementations • 3 Jun 2022 • Fabricio Arend Torres, Marcello Massimo Negri, Monika Nagy-Huber, Maxim Samarin, Volker Roth
Physics-informed Neural Networks (PINNs) have recently emerged as a principled way to include prior physical knowledge in form of partial differential equations (PDEs) into neural networks.
no code implementations • 14 Apr 2022 • Vitali Nesterov, Fabricio Arend Torres, Monika Nagy-Huber, Maxim Samarin, Volker Roth
These networks represent functions that are guaranteed to have connected level sets forming smooth manifolds on the input space.
