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mpnn

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Melty Molecule is a molecular property prediction system that leverages graph neural networks to predict melting points of chemical compounds. The model uses a hybrid architecture combining Principal Neighborhood Aggregation (PNA) and Graph Isomorphism Networks (GIN) with edge updates and virtual node connectivity.

  • Updated Jan 10, 2026
  • Python

Scaffold-split benchmark suite for ADMET property prediction (hERG, solubility, CYP3A4, Caco-2, clearance) with Morgan FP+RF and MPNN baselines, plus ECE/calibration metrics for uncertainty-aware evaluation. PyTorch · RDKit · DeepChem · scikit-learn.

  • Updated Jul 4, 2026

Optical tracking analytics for football: automatic goal detection, possession, pressure, block area, momentum, Voronoi diagrams and animations, plus two self-supervised graph neural networks (GuardiolAI trajectory prediction, MPNN pass receiver selection).

  • Updated Aug 17, 2026
  • Jupyter Notebook

Seven graph neural networks (GCN, MPNN, DCNN, GIN, GAT, GraphSAGE, AttentiveFP) in PyTorch Geometric for molecular property prediction: ESOL solubility from SMILES, with train/predict CLI and tests.

  • Updated Oct 18, 2026
  • Python

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