Model reduction error estimation on Transport equation trajectory manifold Eq 4.4, Init 4.5
0.0085Test ErrorFF-Weld-2
Evaluation results
| Method | Links | |
|---|---|---|
| FF-Weld-2Number of training samples=1802025.12 | 0.0085 | |
| FF-Weld-4Number of training samples=2402025.12 | 0.0094 | |
| FF-Weld-2Number of training samples=302025.12 | 0.0095 | |
| FF-Weld-4Number of training samples=3002025.12 | 0.0102 | |
| FF-Weld-2Number of training samples=902025.12 | 0.0103 | |
| FF-Weld-4Number of training samples=602025.12 | 0.0112 | |
| FF-Weld-2Number of training samples=2702025.12 | 0.0113 | |
| FF-Weld-4Number of training samples=902025.12 | 0.0116 | |
| FF-Weld-2Number of training samples=2402025.12 | 0.0118 | |
| FF-Weld-2Number of training samples=1502025.12 | 0.012 | |
| FF-Weld-2Number of training samples=602025.12 | 0.0125 | |
| FF-Weld-4Number of training samples=1502025.12 | 0.0125 | |
| FF-Weld-4Number of training samples=2102025.12 | 0.0135 | |
| FF-Weld-4Number of training samples=302025.12 | 0.0136 | |
| FF-Weld-2Number of training samples=1202025.12 | 0.0139 | |
| FF-Weld-2Number of training samples=2102025.12 | 0.014 | |
| FF-Weld-4Number of training samples=1202025.12 | 0.0141 | |
| FF-Weld-4Number of training samples=2702025.12 | 0.0141 | |
| FF-Weld-2Number of training samples=3002025.12 | 0.0142 | |
| Conv-Weld-4Number of training samples=902025.12 | 0.0155 | |
| Latent-DONNumber of training samples=602025.12 | 0.0155 | |
| Latent-DONNumber of training samples=302025.12 | 0.0156 | |
| FF-Weld-4Number of training samples=1802025.12 | 0.016 | |
| Conv-Weld-4Number of training samples=602025.12 | 0.0163 | |
| Latent-DONNumber of training samples=1502025.12 | 0.0165 | |
| Conv-Weld-4Number of training samples=302025.12 | 0.0168 | |
| Latent-DONNumber of training samples=2102025.12 | 0.0174 | |
| Conv-Weld-2Number of training samples=1502025.12 | 0.0181 | |
| HDPNumber of training samples=302025.12 | 0.0189 | |
| Conv-Weld-4Number of training samples=2702025.12 | 0.019 | |
| Latent-DONNumber of training samples=1802025.12 | 0.0193 | |
| FF-AENetNumber of training samples=1502025.12 | 0.0195 | |
| FF-AENetNumber of training samples=1202025.12 | 0.0196 | |
| Conv-Weld-2Number of training samples=1802025.12 | 0.0198 | |
| Conv-Weld-4Number of training samples=1502025.12 | 0.0202 | |
| Conv-Weld-4Number of training samples=3002025.12 | 0.0203 | |
| FF-AENetNumber of training samples=602025.12 | 0.0204 | |
| Latent-DONNumber of training samples=2402025.12 | 0.0204 | |
| Latent-DONNumber of training samples=2702025.12 | 0.0207 | |
| Conv-Weld-4Number of training samples=1202025.12 | 0.0212 | |
| FF-AENetNumber of training samples=302025.12 | 0.0215 | |
| FF-AENetNumber of training samples=2402025.12 | 0.0217 | |
| Latent-DONNumber of training samples=1202025.12 | 0.0217 | |
| Latent-DONNumber of training samples=902025.12 | 0.0218 | |
| Conv-Weld-2Number of training samples=302025.12 | 0.0221 | |
| FF-AENetNumber of training samples=902025.12 | 0.0223 | |
| FF-AENetNumber of training samples=1802025.12 | 0.0224 | |
| Conv-Weld-2Number of training samples=2702025.12 | 0.0225 | |
| Conv-Weld-2Number of training samples=602025.12 | 0.0234 | |
| Conv-AENetNumber of training samples=3002025.12 | 0.0234 | |
| Conv-Weld-2Number of training samples=902025.12 | 0.0235 | |
| FF-AENetNumber of training samples=2102025.12 | 0.0245 | |
| Conv-Weld-2Number of training samples=1202025.12 | 0.0248 | |
| Conv-Weld-2Number of training samples=2102025.12 | 0.0248 | |
| Conv-Weld-4Number of training samples=1802025.12 | 0.0248 | |
| FF-AENetNumber of training samples=2702025.12 | 0.0249 | |
| Conv-Weld-2Number of training samples=2402025.12 | 0.025 | |
| Conv-Weld-2Number of training samples=3002025.12 | 0.0268 | |
| Conv-AENetNumber of training samples=2102025.12 | 0.0271 | |
| Conv-Weld-4Number of training samples=2402025.12 | 0.0292 | |
| Conv-AENetNumber of training samples=302025.12 | 0.0298 | |
| Conv-AENetNumber of training samples=2702025.12 | 0.03 | |
| Conv-Weld-4Number of training samples=2102025.12 | 0.0311 | |
| Latent-DONNumber of training samples=3002025.12 | 0.0318 | |
| Conv-AENetNumber of training samples=2402025.12 | 0.0324 | |
| Conv-AENetNumber of training samples=902025.12 | 0.0346 | |
| HDPNumber of training samples=602025.12 | 0.0348 | |
| LDNetNumber of training samples=302025.12 | 0.0359 | |
| FF-AENetNumber of training samples=3002025.12 | 0.0362 | |
| LDNetNumber of training samples=602025.12 | 0.0416 | |
| Conv-AENetNumber of training samples=602025.12 | 0.0427 | |
| Conv-AENetNumber of training samples=1802025.12 | 0.0439 | |
| Conv-AENetNumber of training samples=1502025.12 | 0.0445 | |
| LDNetNumber of training samples=2102025.12 | 0.0453 | |
| LDNetNumber of training samples=1202025.12 | 0.0459 | |
| LDNetNumber of training samples=2702025.12 | 0.0463 | |
| LDNetNumber of training samples=1502025.12 | 0.0472 | |
| LDNetNumber of training samples=1802025.12 | 0.0476 | |
| LDNetNumber of training samples=902025.12 | 0.0492 | |
| LDNetNumber of training samples=2402025.12 | 0.0504 | |
| Conv-AENetNumber of training samples=1202025.12 | 0.0516 | |
| TimeInputNumber of training samples=302025.12 | 0.058 | |
| TimeInputNumber of training samples=902025.12 | 0.0591 | |
| TimeInputNumber of training samples=1802025.12 | 0.061 | |
| TimeInputNumber of training samples=2102025.12 | 0.064 | |
| TimeInputNumber of training samples=2702025.12 | 0.0661 | |
| TimeInputNumber of training samples=602025.12 | 0.0668 | |
| TimeInputNumber of training samples=1202025.12 | 0.0669 | |
| TimeInputNumber of training samples=1502025.12 | 0.0679 | |
| HDPNumber of training samples=3002025.12 | 0.0697 | |
| TimeInputNumber of training samples=2402025.12 | 0.0703 | |
| HDPNumber of training samples=902025.12 | 0.0767 | |
| LDNetNumber of training samples=3002025.12 | 0.0829 | |
| TimeInputNumber of training samples=3002025.12 | 0.0921 | |
| HDPNumber of training samples=1202025.12 | 0.1062 | |
| HDPNumber of training samples=1502025.12 | 0.1366 | |
| HDPNumber of training samples=1802025.12 | 0.148 | |
| HDPNumber of training samples=2102025.12 | 0.1629 | |
| PCA-WeldNet-4Number of training samples=1502025.12 | 0.1697 | |
| PCA-WeldNet-4Number of training samples=3002025.12 | 0.1705 |