Deriving Compact and Modular Physics-Informed Neural Network Architectures for Solving Partial Differential Equations

Brain-inspired neural network techniques can be used to derive compact and modular PINN architectures that minimize computing and memory resources while providing accurate solutions to partial differential equations.