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).

This repository distributes the trained FUSE-RT checkpoints for the original 179-method RepoRT cohort. It contains 180 checkpoints across 18 experimental configurations, with 10 seeds per configuration.

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.

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

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