A unified framework combining physics-informed neural networks with finite element methods via functional Gauss-Newton problems and Petrov-Galerkin discretization.
See LICENSE filePINNfinite element methodPDE solver
A 36M-parameter neural network solver for partial differential equations based on U-Net architecture, enabling data-driven solving and prediction of PDE systems
A code perturbation dataset with 256 PDE solver implementations comprising 64 base programs and 4 lexical perturbation variants each, designed for evaluating LLM understanding of physics simulation code.
See LICENSE filePDE solvercode perturbationLLM evaluation
