Time Series Forecasting On Etth2 336 2
Metrics
MAE
MSE
Results
Performance results of various models on this benchmark
| Paper Title | Code | |||
|---|---|---|---|---|
| Transformer | 0.3805 | 0.2191 | Long-term series forecasting with Query Selector -- efficient model of sparse attention | |
| QuerySelector | 0.371 | 0.2088 | Long-term series forecasting with Query Selector -- efficient model of sparse attention | |
| DLinear | 0.367 | 0.209 | Are Transformers Effective for Time Series Forecasting? | |
| FiLM | 0.367 | 0.204 | FiLM: Frequency improved Legendre Memory Model for Long-term Time Series Forecasting | |
| NLinear | 0.355 | 0.194 | Are Transformers Effective for Time Series Forecasting? | |
| SegRNN | 0.345 | 0.18 | SegRNN: Segment Recurrent Neural Network for Long-Term Time Series Forecasting | |
| PatchTST/64 | 0.336 | 0.171 | A Time Series is Worth 64 Words: Long-term Forecasting with Transformers | |
| PatchMixer | 0.332 | 0.166 | PatchMixer: A Patch-Mixing Architecture for Long-Term Time Series Forecasting | |
| SCINet | 0.329 | 0.166 | SCINet: Time Series Modeling and Forecasting with Sample Convolution and Interaction | |
| Informer | 0.323 | 0.166 | Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting |
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