705 citations · 1.4k across the 22 of their papers we have counts for
4 papers · 1 filter
Fast PDE-constrained optimization via self-supervised operator learning
Sifan Wang, Mohamed Aziz Bhouri, Paris Perdikaris
Design and optimal control problems are among the fundamental, ubiquitous tasks we face in science and engineering. In both cases, we aim to represent and optimize an unknown (blac…
Improved architectures and training algorithms for deep operator networks
Sifan Wang, Hanwen Wang, Paris Perdikaris
Operator learning techniques have recently emerged as a powerful tool for learning maps between infinite-dimensional Banach spaces. Trained under appropriate constraints, they can…
Long-time integration of parametric evolution equations with physics-informed DeepONets
Sifan Wang, Paris Perdikaris
Ordinary and partial differential equations (ODEs/PDEs) play a paramount role in analyzing and simulating complex dynamic processes across all corners of science and engineering. I…
Learning the solution operator of parametric partial differential equations with physics-informed DeepOnets
Sifan Wang, Hanwen Wang, Paris Perdikaris
Deep operator networks (DeepONets) are receiving increased attention thanks to their demonstrated capability to approximate nonlinear operators between infinite-dimensional Banach…