Time Series Forecasting on ELC
0.175MSEδ-Adapter
Evaluation results
| Method | Links | |
|---|---|---|
| δ-AdapterBackbone Model=DistPred, Variant=Ada-X+Y2026.01 | 0.175 | |
| LoRABackbone Model=DistPred2026.01 | 0.18 | |
| δ-AdapterBackbone Model=iTransformer, Variant=Ada-X+Y2026.01 | 0.18 | |
| OfflineBackbone Model=DistPred2026.01 | 0.182 | |
| SOLIDBackbone Model=DistPred2026.01 | 0.182 | |
| TAFASBackbone Model=DistPred2026.01 | 0.182 | |
| LoRABackbone Model=iTransformer2026.01 | 0.186 | |
| OfflineBackbone Model=iTransformer2026.01 | 0.19 | |
| SOLIDBackbone Model=iTransformer2026.01 | 0.19 | |
| TAFASBackbone Model=iTransformer2026.01 | 0.19 | |
| OneNetBackbone Model=Others2026.01 | 0.417 | |
| δ-AdapterBackbone Model=Autoformer, Variant=Ada-X+Y2026.01 | 0.478 | |
| SOLIDBackbone Model=Autoformer2026.01 | 0.502 | |
| TAFASBackbone Model=Autoformer2026.01 | 0.51 | |
| OfflineBackbone Model=Autoformer2026.01 | 0.515 | |
| FSNetBackbone Model=Others2026.01 | 0.537 |