Tackling High-Dimensional PDEs with Physics-Informed Neural Networks

Physics-Informed Neural Networks (PINNs) are scaled up using Stochastic Dimension Gradient Descent (SDGD) to efficiently solve high-dimensional PDEs, demonstrating fast convergence and reduced memory costs.