Traffic Prediction On Pems07
Métriques
MAE@1h
Résultats
Résultats de performance de divers modèles sur ce benchmark
Tableau comparatif
| Nom du modèle | MAE@1h |
|---|---|
| online-test-time-adaptation-of-spatial | 19.62 |
| spatial-temporal-graph-ode-networks-for | 22.99 |
| pdg2seq-periodic-dynamic-graph-to-sequence | 19.28 |
| when-spatio-temporal-meet-wavelets | 19.94 |
| pattern-matching-dynamic-memory-network-for-1 | 19.35 |
| spatio-temporal-decoupled-masked-pre-training | 18.31 |
| attention-based-spatial-temporal-graph | 28.05 |
| pdformer-propagation-delay-aware-dynamic-long | 19.83 |
| structured-time-series-prediction-without | 21.62 |
| a-decomposition-dynamic-graph-convolutional | 19.79 |
| a-correlation-information-based | 19.62 |
| spatio-temporal-adaptive-embedding-makes | 19.14 |
| spatio-temporal-graph-convolutional-networks | 25.38 |
| spatial-temporal-synchronous-graph | 24.26 |
| a-gated-mlp-architecture-for-learning | 19.45 |
| spatial-temporal-fusion-graph-neural-networks | 22.07 |
| pattern-matching-dynamic-memory-network-for-1 | 19.18 |