Time Series Forecasting on GIFT-Eval 05/18/2025 snapshot (test)
0.671MASEPer-dataset
Evaluation Results
| Method | Links | |
|---|---|---|
| Per-datasetType=ERA2025.09 | 0.671 | |
| TTM-R2-FinetunedType=fine-tuned2025.09 | 0.679 | |
| timesfm_2_0_500mType=pretrained2025.09 | 0.68 | |
| TabPFN-TSType=pretrained2025.09 | 0.692 | |
| chronos_bolt_baseType=pretrained2025.09 | 0.725 | |
| UnifiedType=ERA2025.09 | 0.734 | |
| chronos_bolt_smallType=pretrained2025.09 | 0.738 | |
| PatchTSTType=deep-learning2025.09 | 0.762 | |
| TEMPO_ensembleType=fine-tuned2025.09 | 0.773 | |
| VisionTSType=pretrained2025.09 | 0.775 | |
| Chronos_largeType=pretrained2025.09 | 0.781 | |
| Moirai_largeType=pretrained2025.09 | 0.785 | |
| Chronos_baseType=pretrained2025.09 | 0.786 | |
| Chronos_smallType=pretrained2025.09 | 0.8 | |
| Moirai_baseType=pretrained2025.09 | 0.809 | |
| TFTType=deep-learning2025.09 | 0.822 | |
| N-BEATSType=deep-learning2025.09 | 0.842 | |
| Moirai_smallType=pretrained2025.09 | 0.849 | |
| TTM-R2-ZeroshotType=pretrained2025.09 | 0.915 | |
| DLinearType=deep-learning2025.09 | 0.952 | |
| Auto_ArimaType=statistical2025.09 | 0.964 | |
| TimesFMType=pretrained2025.09 | 0.967 | |
| TTM-R1-ZeroshotType=pretrained2025.09 | 0.969 | |
| Auto_ThetaType=statistical2025.09 | 0.978 | |
| TIDEType=deep-learning2025.09 | 0.98 | |
| Seasonal_NaiveType=statistical2025.09 | 1 | |
| TimerType=pretrained2025.09 | 1.019 | |
| Auto_ETSType=statistical2025.09 | 1.088 | |
| Lag-LlamaType=pretrained2025.09 | 1.102 | |
| DeepARType=deep-learning2025.09 | 1.206 | |
| NaiveType=statistical2025.09 | 1.26 | |
| CrossformerType=deep-learning2025.09 | 2.31 |