Python library supporting Discrete Variational Formulations and training solutions with Collocation-based Robust Variational Physics Informed Neural Networks (DVF-CRVPINN)

This paper explores solving Partial Differential Equations (PDEs) using discrete weak formulations and a discrete neural network representation. It proposes a Python environment and a DVF-CRVPINN approach for training solutions, applying discrete automatic differentiation for equations like 2D Stokes.