Multi-Architecture Coupled Ensemble Physics-Informed Neural Networks (MACE-PINN) for solving coupled partial differential equations. Implements parallel subnetworks with Fourier embeddings and adaptive loss weighting for Gray-Scott and Ginzburg-Landau reaction-diffusion systems.

Physics-Informed Neural Networks (PINNs) for solving coupled first-order partial differential equations, validated against a classical Finite Difference Method (FDM) benchmark.