PINA and PINN
These are competitors offering alternative PyTorch-based implementations of PINNs at different maturity levels—PINA provides a more comprehensive framework with advanced modeling capabilities, while the simpler implementation serves educational or minimal-dependency use cases.
About PINA
mathLab/PINA
Physics-Informed Neural networks for Advanced modeling
Builds on PyTorch, PyTorch Lightning, and PyTorch Geometric to provide modular Problem, Model, Solver, and Trainer APIs for both supervised learning and physics-informed tasks. Supports Neural Operators and graph-based architectures, with automatic differentiation for constraint enforcement (e.g., differential equations, boundary conditions) and multi-device training via PyTorch Lightning's distributed backend.
About PINN
nanditadoloi/PINN
Simple PyTorch Implementation of Physics Informed Neural Network (PINN)
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