pinn-rk provides Runge-Kutta physics-informed neural networks with time-discrete losses in PyTorch. It focuses on Gauss, Radau and Lobatto style formulations for scientific machine learning problems where temporal discretization is part of the modelling choice.
Install
1
pip install pinn-rk
Project Links
- PyPI: pinn-rk
- Documentation: repository documentation
- Source: github.com/DiogoRibeiro7/pinn-rk
- Issues: github.com/DiogoRibeiro7/pinn-rk/issues
- Discussions: github.com/DiogoRibeiro7/pinn-rk/discussions
- Changelog: CHANGELOG.md
Package Metadata
- Current release:
0.6.0 - Requires Python:
>=3.10,<3.13 - License: MIT
Where It Fits
Use this package when the learning problem depends on time-stepping choices, numerical integration structure or a physics-informed loss that should be explicit and inspectable.