paper-with-me

Time Series Forecasting 벤치마크

Time Series Forecasting on ETTm2 (96) Multivariate

18개 결과 · ⬇ CSV · JSON

MSE 낮을수록 좋음

0.153 0.16 0.167 0.174 0.181 2023-05 2026-11 RLinear — 0.164 (2023-05-18) RLinear — 0.164 (2023-05-18) SCNN — 0.163 (2023-05-22) SCNN — 0.163 (2023-05-22) TSMixer — 0.164 (2023-06-14) TSMixer — 0.164 (2023-06-14) MoLE-DLinear — 0.168 (2023-12-11) MoLE-DLinear — 0.168 (2023-12-11) TEFN — 0.181 (2024-05-10) TEFN — 0.181 (2024-05-10) PRformer — 0.162 (2024-08-20) PRformer — 0.162 (2024-08-20) LTBoost (drop_last=false) — 0.156 (2024-10-21) LTBoost (drop_last=false) — 0.156 (2024-10-21) DiPE-Linear — 0.162 (2024-11-26) DiPE-Linear — 0.162 (2024-11-26) xPatch — 0.153 (2024-12-23) xPatch — 0.153 (2024-12-23) RLinear — 0.164 (2023-05-18) SCNN — 0.163 (2023-05-22) PRformer — 0.162 (2024-08-20) LTBoost (drop_last=false) — 0.156 (2024-10-21) xPatch — 0.153 (2024-12-23)
RankModel MSEMAE PaperCodeYear
1 xPatch 0.1530.240 xPatch: Dual-Stream Time Series Forecasting with Exponential Seasonal-Trend Decomposition stitsyuk/xpatch 2024
2 LTBoost (drop_last=false) 0.1560.243 LTBoost: Boosted Hybrids of Ensemble Linear and Gradient Algorithms for the Long-term Time Series Forecasting hubtru/LTBoost 2024
3 PRformer 0.162– PRformer: Pyramidal Recurrent Transformer for Multivariate Time Series Forecasting usualheart/prformer 2024
3 DiPE-Linear 0.162– Disentangled Interpretable Representation for Efficient Long-term Time Series Forecasting wintertee/dipe-linear 2024
5 SCNN 0.163– Disentangling Structured Components: Towards Adaptive, Interpretable and Scalable Time Series Forecasting JLDeng/SCNN 2023
6 RLinear 0.1640.253 Revisiting Long-term Time Series Forecasting: An Investigation on Linear Mapping plumprc/rtsf 2023
6 TSMixer 0.1640.255 TSMixer: Lightweight MLP-Mixer Model for Multivariate Time Series Forecasting ibm/tsfm 2023
8 MoLE-DLinear 0.168– Mixture-of-Linear-Experts for Long-term Time Series Forecasting rogerni/mole 2023
9 TEFN 0.1810.264 Time Evidence Fusion Network: Multi-source View in Long-Term Time Series Forecasting WenjieDu/PyPOTS · ztxtech/Time-Evidence-Fusion-Network 2024
10 xPatch 0.1530.240 xPatch: Dual-Stream Time Series Forecasting with Exponential Seasonal-Trend Decomposition stitsyuk/xpatch 2024
11 LTBoost (drop_last=false) 0.1560.243 LTBoost: Boosted Hybrids of Ensemble Linear and Gradient Algorithms for the Long-term Time Series Forecasting hubtru/LTBoost 2024
12 PRformer 0.162– PRformer: Pyramidal Recurrent Transformer for Multivariate Time Series Forecasting usualheart/prformer 2024
12 DiPE-Linear 0.162– Disentangled Interpretable Representation for Efficient Long-term Time Series Forecasting wintertee/dipe-linear 2024
14 SCNN 0.163– Disentangling Structured Components: Towards Adaptive, Interpretable and Scalable Time Series Forecasting JLDeng/SCNN 2023
15 RLinear 0.1640.253 Revisiting Long-term Time Series Forecasting: An Investigation on Linear Mapping plumprc/rtsf 2023
15 TSMixer 0.1640.255 TSMixer: Lightweight MLP-Mixer Model for Multivariate Time Series Forecasting ibm/tsfm 2023
17 MoLE-DLinear 0.168– Mixture-of-Linear-Experts for Long-term Time Series Forecasting rogerni/mole 2023
18 TEFN 0.1810.264 Time Evidence Fusion Network: Multi-source View in Long-Term Time Series Forecasting WenjieDu/PyPOTS · ztxtech/Time-Evidence-Fusion-Network 2024
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