Shear moduli prediction on Materials Project (test)
0.065MAE (log10 GPa)PotNet
Evaluation results
| Method | Links | |||
|---|---|---|---|---|
| PotNet2023.06 | 0.065 | — | — | |
| Matformer2023.06 | 0.073 | — | — | |
| Matformer2022.09 | 0.073 | — | — | |
| GATGNN2023.06 | 0.075 | — | — | |
| GATGNNSource=Retrained2022.09 | 0.075 | — | — | |
| CGCNN2023.06 | 0.077 | — | — | |
| CGCNNSource=Retrained2022.09 | 0.077 | — | — | |
| ALIGNN2023.06 | 0.078 | — | — | |
| ALIGNNSource=Retrained2022.09 | 0.078 | — | — | |
| MEGNetElements=89, Training structures=46642018.12 | 0.079 | — | — | |
| MEGNETSource=Original paper results2022.09 | 0.079 | — | — | |
| CGCNNElements=87, Training structures=20412018.12 | 0.087 | — | — | |
| CGCNNSource=Original paper results2022.09 | 0.087 | — | — | |
| SchNet2023.06 | 0.099 | — | — | |
| MEGNET2023.06 | 0.099 | — | — | |
| SchNetSource=Retrained, Radius=32-th smallest distance2022.09 | 0.099 | — | — | |
| MEGNETSource=Retrained, Radius=12-th smallest distance, Batch size=642022.09 | 0.099 | — | — | |
| CGCNN# of train data=2041, Unit=log(GPa)2017.10 | — | 0.087 | — | |
| DFT# of train data=2041, Unit=log(GPa)2017.10 | — | — | 0.069 |