Interatomic potential modeling on Revised MD17 (val test)
6.6Aspirin Force ErrorMACE
Evaluation results
| Method | Links | ||||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| MACENtrain=1000, Training dataset=rMD172022.06 | 6.6 | 2.2 | 1.2 | 3 | 0.4 | 0.3 | 0.4 | 2.1 | 0.8 | 4.1 | 0.5 | 1.6 | 1.3 | 4.8 | 0.9 | 3.1 | 0.5 | 1.5 | 0.5 | 2.1 | |
| AllegroNtrain=1000, Training dataset=rMD172022.06 | 7.3 | 2.3 | 1.2 | 2.6 | 0.3 | 0.2 | 0.4 | 2.1 | 0.6 | 3.6 | 0.2 | 0.9 | 1.5 | 4.9 | 0.9 | 2.9 | 0.4 | 1.8 | 0.6 | 1.8 | |
| NequIPNtrain=1000, Training dataset=rMD172022.06 | 8.2 | 2.3 | 0.7 | 2.9 | 0.04 | 0.3 | 0.4 | 2.8 | 0.8 | 5.1 | 0.9 | 1.3 | 1.4 | 5.9 | 0.7 | 4 | 0.3 | 1.6 | 0.4 | 3.1 | |
| BOTNetNtrain=1000, Training dataset=rMD172022.06 | 8.5 | 2.3 | 0.7 | 3.3 | 0.03 | 0.3 | 0.4 | 3.2 | 0.8 | 5.8 | 0.2 | 1.8 | 1.3 | 5.8 | 0.8 | 4.3 | 0.3 | 1.9 | 0.4 | 3.2 | |
| GemNet (T/Q)Ntrain=1000, Training dataset=rMD172022.06 | 9.5 | — | — | — | — | 0.5 | — | 3.6 | — | 6.6 | — | 1.9 | — | — | — | 5.3 | — | 2.2 | — | 3.8 | |
| NewtonNetNtrain=1000, Training dataset=Original MD172022.06 | 15.1 | 7.3 | 6.1 | 5.9 | — | — | 2.6 | 9.1 | 4.1 | 14 | 5.2 | 3.6 | 6.1 | 11.4 | 4.9 | 8.5 | 4.1 | 3.8 | 4.6 | 6.4 | |
| PaiNNNtrain=1000, Training dataset=rMD172022.06 | 16.1 | 6.9 | — | — | — | — | 2.7 | 10 | 3.9 | 13.8 | 5.1 | 3.6 | — | — | 4.9 | 9.1 | 4.2 | 4.4 | 4.5 | 6.1 | |
| ACENtrain=1000, Training dataset=rMD172022.06 | 17.9 | 6.1 | 3.6 | 10.9 | 0.04 | 0.5 | 1.2 | 7.3 | 1.7 | 11.1 | 0.9 | 5.1 | 4 | 12.7 | 1.8 | 9.3 | 1.1 | 6.5 | 1.1 | 6.6 | |
| FCHLNtrain=1000, Training dataset=rMD172022.06 | 20.9 | 6.2 | 2.8 | 10.8 | 0.35 | 2.6 | 0.9 | 6.2 | 1.5 | 10.3 | 1.2 | 6.5 | 2.9 | 12.3 | 1.8 | 9.5 | 1.7 | 8.8 | 0.6 | 4.2 | |
| DimeNetNtrain=1000, Training dataset=Original MD172022.06 | 21.6 | 8.8 | — | — | 3.4 | 8.1 | 2.8 | 10 | 4.5 | 16.6 | 5.3 | 9.3 | — | — | 5.8 | 16.2 | 4.4 | 9.4 | 5 | 13.1 | |
| ANINtrain=1000, Training dataset=rMD172022.06 | 40.6 | 16.6 | 15.9 | 35.4 | 3.3 | 10 | 2.5 | 13.4 | 4.6 | 24.5 | 11.3 | 29.2 | 11.5 | 30.4 | 9.2 | 29.7 | 7.7 | 24.3 | 5.1 | 21.4 | |
| MACENtrain=50, Training dataset=rMD172022.06 | 43.9 | 17 | 5.4 | 17.7 | 0.7 | 2.7 | 6.7 | 32.6 | 10 | 43.3 | 2.1 | 9.2 | 9.7 | 31.5 | 6.5 | 28.4 | 3.1 | 12.1 | 4.4 | 25.9 | |
| GAPNtrain=1000, Training dataset=rMD172022.06 | 44.9 | 17.7 | 8.5 | 24.5 | 0.75 | 6 | 3.5 | 18.1 | 4.8 | 26.4 | 3.8 | 16.5 | 8.5 | 28.9 | 5.6 | 24.7 | 4 | 17.8 | 3 | 17.6 | |
| NequIPNtrain=50, Training dataset=rMD172022.06 | 52 | 19.5 | 6 | 20 | 0.6 | 2.9 | 8.7 | 40.2 | 12.7 | 52.5 | 2.1 | 10 | 14.3 | 39.7 | 8 | 35 | 3.3 | 15.1 | 7.3 | 40.1 | |
| ACENtrain=50, Training dataset=rMD172022.06 | 63.8 | 26.2 | 9 | 28.8 | 0.2 | 2.7 | 8.6 | 43 | 12.8 | 63.5 | 3.8 | 19.7 | 13.6 | 45.7 | 8.9 | 41.7 | 5.3 | 27.1 | 6.5 | 36.2 |