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Model for kpoint_length_unit

  • Description: This is a benchmark to evaluate how accurately an AI model can predict the converged k-point length for DFT calculations 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/s41524-023-01012-9;https://hackingmaterials.lbl.gov/matminer, https://hackingmaterials.lbl.gov/matminer/, https://www.nature.com/articles/s41524-021-00650-1, https://doi.org/10.1103/PhysRevMaterials.2.083801, https://doi.org/10.48550/arXiv.2305.11842, https://www.nature.com/articles/s41524-020-00440-1, https://github.com/aimat-lab/gcnn_keras

Model benchmarks

Model nameDataset MAE Team name Dataset size Date submitted Notes
kgcnn_schnetdft_3d10.1022kgcnn5539209-26-2023CSV, JSON, run.sh, Info
kgcnn_coNGNdft_3d9.3459kgcnn5539205-06-2023CSV, JSON, run.sh, Info
matminer_xgboostdft_3d9.047UofT5539205-22-2023CSV, JSON, run.sh, Info
alignn_modeldft_3d9.5146ALIGNN5539201-14-2023CSV, JSON, run.sh, Info
kgcnn_megnetdft_3d10.3826kgcnn5539205-06-2023CSV, JSON, run.sh, Info
cfid_chemdft_3d11.5692JARVIS5539201-14-2023CSV, JSON, run.sh, Info
matminer_lgbmdft_3d9.3275Matminer5539201-14-2023CSV, JSON, run.sh, Info
matminer_rfdft_3d9.1665UofT5539205-22-2023CSV, JSON, run.sh, Info
kgcnn_coGNdft_3d9.5722kgcnn5539205-06-2023CSV, JSON, run.sh, Info
cfiddft_3d9.7085JARVIS5539201-14-2023CSV, JSON, run.sh, Info
kgcnn_dimenetPPdft_3d11.8875kgcnn5539205-06-2023CSV, JSON, run.sh, Info
kgcnn_cgcnndft_3d9.8748kgcnn5539209-26-2023CSV, JSON, run.sh, Info