Model for spillage

• Description: This is a benchmark to evaluate how accurately an AI model can predict the spin-orbit spillage using the JARVIS-DFT (dft_3d) dataset. The dataset contains different types of chemical formula and atomic structures. Here we use mean absolute error (MAE) to compare models with respect to DFT accuracy.
  

Reference(s): https://www.nature.com/articles/s41524-020-00440-1, https://doi.org/10.1103/PhysRevMaterials.2.083801, https://www.nature.com/articles/s41524-023-01012-9;https://hackingmaterials.lbl.gov/matminer, https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.120.145301, https://doi.org/10.48550/arXiv.2305.11842, https://www.nature.com/articles/s41524-021-00650-1, https://hackingmaterials.lbl.gov/matminer/, https://github.com/aimat-lab/gcnn_keras

Model benchmarks

Model name	Dataset	MAE	Team name	Dataset size	Date submitted	Notes
kgcnn_coNGN	dft_3d	0.3463	kgcnn	11375	05-06-2023	CSV, JSON, run.sh, Info
kgcnn_cgcnn	dft_3d	0.3844	kgcnn	11375	09-26-2023	CSV, JSON, run.sh, Info
matminer_rf	dft_3d	0.3615	UofT	11375	05-22-2023	CSV, JSON, run.sh, Info
kgcnn_dimenetPP	dft_3d	0.4137	kgcnn	11375	05-06-2023	CSV, JSON, run.sh, Info
cfid	dft_3d	0.3867	JARVIS	11375	01-14-2023	CSV, JSON, run.sh, Info
alignn_model	dft_3d	0.351	ALIGNN	11375	01-14-2023	CSV, JSON, run.sh, Info
matminer_lgbm	dft_3d	0.3806	Matminer	11375	01-14-2023	CSV, JSON, run.sh, Info
kgcnn_megnet	dft_3d	0.3904	kgcnn	11375	05-06-2023	CSV, JSON, run.sh, Info
cgcnn_model	dft_3d	0.3965	CGCNN	11375	01-14-2023	CSV, JSON, run.sh, Info
matminer_xgboost	dft_3d	0.3592	UofT	11375	05-22-2023	CSV, JSON, run.sh, Info
kgcnn_coGN	dft_3d	0.3609	kgcnn	11375	05-06-2023	CSV, JSON, run.sh, Info
cfid_chem	dft_3d	0.3957	JARVIS	11375	01-14-2023	CSV, JSON, run.sh, Info
kgcnn_schnet	dft_3d	0.3622	kgcnn	11375	09-26-2023	CSV, JSON, run.sh, Info