torch-geometric
Graph Neural Networks (PyG). Node/graph classification, link prediction, GCN, GAT, GraphSAGE, heterogeneous graphs, molecular property prediction, for geometric deep learning.
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Graph Neural Networks (PyG). Node/graph classification, link prediction, GCN, GAT, GraphSAGE, heterogeneous graphs, molecular property prediction, for geometric deep learning.
Materials science toolkit. Crystal structures (CIF, POSCAR), phase diagrams, band structure, DOS, Materials Project integration, format conversion, for computational materials science.
Modern RDKit workflows for cheminformatics, including molecular fingerprints, drawing, and property calculations. Use when working with molecules, SMILES, molecular fingerprints (Morgan, ECFP, RDKit, atom pairs...
Machine learning workflows for molecular data. Use when building ML models with molecules, splitting datasets, selecting fingerprints for ML, avoiding data leakage, or doing scaffold-based train/test splits. Co...
Python package and environment management using uv and mamba. Use when installing packages, creating virtual environments, setting up new projects, or managing dependencies. NOT for general Python coding questi...
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