A carefully curated collection of high-quality libraries, projects, tutorials, research papers, and other essential resources focused on Physics-Informed Machine Learning (PIML) and Physics-Informed Neural Networks (PINNs).
In this repository, we would see different available libraries for Exploratory Data Analysis
Main codes for half-cell model, PINN and co-kriging implemented for physics-informed degradation diagnostics project: https://doi.org/10.1016/j.ensm.2024.103343
a tailored physics-informed neural network for SPDE
MLOps-driven machine learning engine with deep user and social network insights for personalized, real-time product suggestions. A Physics Informed Machine Learning Project.
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