Time Series Forecasting on ETTh1 10% training data (test)
0.421MSEFiCoTS
Evaluation Results
| Method | Links | ||
|---|---|---|---|
| FiCoTSInput sequence length=512, Predictive lengths={96, 192, 336, 720}, Method Category=LLM-based, Training data percentage=10%2025.11 | 0.421 | 0.438 | |
| TimeVLMInput sequence length=512, Predictive lengths={96, 192, 336, 720}, Method Category=LLM-based, Training data percentage=10%2025.11 | 0.431 | 0.442 | |
| TIME-LLMParameters (M)=6.46, Memory (MiB)=3907, Eff.*MSE=0.43, Eff.*MAE=0.402026.03 | 0.56 | 0.52 | |
| GPT4TSInput sequence length=512, Predictive lengths={96, 192, 336, 720}, Method Category=LLM-based, Training data percentage=10%2025.11 | 0.59 | 0.525 | |
| GPT4TSParameters (M)=11.7, Memory (MiB)=371.0, Eff.*MSE=0.21, Eff.*MAE=0.212026.03 | 0.59 | 0.53 | |
| TESTParameters (M)=2.00, Memory (MiB)=701, Eff.*MSE=1.24, Eff.*MAE=1.262026.03 | 0.59 | 0.53 | |
| S2IP-LLMInput sequence length=512, Predictive lengths={96, 192, 336, 720}, Method Category=LLM-based, Training data percentage=10%2025.11 | 0.593 | 0.529 | |
| PatchTSTInput sequence length=512, Predictive lengths={96, 192, 336, 720}, Method Category=Transformer-based, Training data percentage=10%2025.11 | 0.633 | 0.542 | |
| FEDformerInput sequence length=512, Predictive lengths={96, 192, 336, 720}, Method Category=Transformer-based, Training data percentage=10%2025.11 | 0.639 | 0.561 | |
| EFDformerParameters (M)=16.8, Memory (MiB)=87.8, Eff.*MSE=0.12, Eff.*MAE=0.122026.03 | 0.64 | 0.56 | |
| One-for-AllParameters (M)=0.55, Memory (MiB)=2.2, Eff.*MSE=4.37, Eff.*MAE=4.482026.03 | 0.65 | 0.55 | |
| DLinearInput sequence length=512, Predictive lengths={96, 192, 336, 720}, Method Category=Non-Transformer-based, Training data percentage=10%2025.11 | 0.691 | 0.6 | |
| AutoformerParameters (M)=10.53, Memory (MiB)=62.6, Eff.*MSE=0.13, Eff.*MAE=0.162026.03 | 0.7 | 0.6 | |
| AutoformerInput sequence length=512, Predictive lengths={96, 192, 336, 720}, Method Category=Transformer-based, Training data percentage=10%2025.11 | 0.702 | 0.596 | |
| TimeLLMInput sequence length=512, Predictive lengths={96, 192, 336, 720}, Method Category=LLM-based, Training data percentage=10%2025.11 | 0.785 | 0.553 | |
| TimesNetInput sequence length=512, Predictive lengths={96, 192, 336, 720}, Method Category=Non-Transformer-based, Training data percentage=10%2025.11 | 0.869 | 0.628 | |
| TimesNetParameters (M)=0.63, Memory (MiB)=2.9, Eff.*MSE=3.02, Eff.*MAE=3.462026.03 | 0.87 | 0.63 | |
| iTransformerInput sequence length=512, Predictive lengths={96, 192, 336, 720}, Method Category=Transformer-based, Training data percentage=10%2025.11 | 0.91 | 0.86 | |
| TStationaryParameters (M)=2.02, Memory (MiB)=13.2, Eff.*MSE=0.88, Eff.*MAE=1.052026.03 | 0.92 | 0.64 | |
| ETSformerInput sequence length=512, Predictive lengths={96, 192, 336, 720}, Method Category=Transformer-based, Training data percentage=10%2025.11 | 1.18 | 0.834 | |
| ETSformerParameters (M)=5.28, Memory (MiB)=31.4, Eff.*MSE=0.25, Eff.*MAE=0.312026.03 | 1.18 | 0.83 | |
| InformerParameters (M)=11.33, Memory (MiB)=65.8, Eff.*MSE=0.04, Eff.*MAE=0.092026.03 | 1.2 | 0.81 | |
| ReformerParameters (M)=5.80, Memory (MiB)=33.4, Eff.*MSE=0.08, Eff.*MAE=0.092026.03 | 1.25 | 0.83 |