PhysicsInformedML.jl
AI/ML Toolkit • 2021 • Active
PhysicsInformedML.jl contains reusable subroutines for incorporating physical constraints into learning pipelines and model diagnostics.
PhysicsInformedML.jl packages reusable subroutines for bringing scientific and physical constraints into machine learning workflows.
It complements broader SmartTensors-style workflows by helping combine data-driven learning with domain knowledge and model diagnostics.
The package is designed for Julia-based scientific ML pipelines where interpretability and physical consistency matter.
Capabilities
- Reusable physics-informed ML building blocks
- Supports science-informed diagnostics and workflow integration
- Designed for Julia scientific machine learning pipelines
Physics-Informed AIScientific MLJulia