Time Series Forecasting On Etth2 192 2
Metrics
MAE
MSE
Results
Performance results of various models on this benchmark
Model Name | MAE | MSE | Paper Title | Repository |
|---|---|---|---|---|
| PatchMixer | 0.305 | 0.147 | PatchMixer: A Patch-Mixing Architecture for Long-Term Time Series Forecasting | |
| NLinear | 0.324 | 0.169 | Are Transformers Effective for Time Series Forecasting? | |
| SegRNN | 0.317 | 0.158 | SegRNN: Segment Recurrent Neural Network for Long-Term Time Series Forecasting | |
| FiLM | 0.335 | 0.182 | FiLM: Frequency improved Legendre Memory Model for Long-term Time Series Forecasting | |
| DLinear | 0.329 | 0.176 | Are Transformers Effective for Time Series Forecasting? | |
| PatchTST/64 | 0.329 | 0.171 | A Time Series is Worth 64 Words: Long-term Forecasting with Transformers |
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