PDE-NetGen 1.0: from symbolic PDE representations of physical processes to trainable neural network representationsphysics.comp-ph
PDE-NetGen converts physical equations to neural networks for various scientific problems.
problem Bridging physics and deep learning for efficient neural network architectures.
method Combines symbolic calculus and neural network generation to translate PDEs into NN architectures.
result Generates compact, computationally-efficient physics-informed NN architectures.