Learning Operators of Geometry with an Interface Autoencoder
ScientificML
Proposes Interface Autoencoder (IAE) for learning neural operators on geometry-dependent PDEs, representing interface-function states in a fixed domain via finite projection codes.
New See LICENSE file Neural OperatorsPDEInterface Autoencoder