sciai-lab/structures25

Trained checkpoints for the ICLR 2026 paper A Function-Centric Graph Neural Network Approach For Predicting Electron Densities.

This repository provides four SCIAI-DFT models for density optimization and geometry optimization with machine-learned orbital-free density functional theory (ML-OFDFT).

- Project page - Try Packora (live demo) - Paper - Code - Dataset manifests - Hugging Face collection

State-of-the-Art Geometric GNN for Predicting Molecular Properties

Predict olfactory descriptors from SMILES strings. A GINE-based graph neural network trained on the Leffingwell PMP dataset, reproducing the Principal Odor Map (POM) approach.

End-to-end molecular dynamics engine built on PyTorch, enabling differentiable simulations with neural network potentials and GPU acceleration for machine learning-accelerated molecular dynamics (MIT License, 707+ stars)