Multifidelity domain decomposition-based physics-informed neural networks and operators for time-dependent problems

Alexander Heinlein, Amanda A. Howard, Damien Beecroft +1

Multiscale problems are challenging for neural network-based discretizations of differential equations, such as physics-informed neural networks (PINNs). This can be (partly) attri…