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HyperAI超神经

Time Series Forecasting On Etth2 720 2

评估指标

MAE

MSE

评测结果

各个模型在此基准测试上的表现结果

模型名称	MAE	MSE	Paper Title	Repository
Transformer	0.434	0.2853	Long-term series forecasting with Query Selector -- efficient model of sparse attention	-
PatchMixer	0.374	0.217	PatchMixer: A Patch-Mixing Architecture for Long-Term Time Series Forecasting	-
FiLM	0.396	0.241	FiLM: Frequency improved Legendre Memory Model for Long-term Time Series Forecasting	-
Informer	0.338	0.181	Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting	-
PatchTST/64	0.38	0.223	A Time Series is Worth 64 Words: Long-term Forecasting with Transformers	-
SegRNN	0.365	0.205	SegRNN: Segment Recurrent Neural Network for Long-Term Time Series Forecasting	-
NLinear	0.381	0.225	Are Transformers Effective for Time Series Forecasting?	-
SCINet	0.429	0.286	SCINet: Time Series Modeling and Forecasting with Sample Convolution and Interaction	-
AutoCon	0.344	0.177	Self-Supervised Contrastive Learning for Long-term Forecasting	-
QuerySelector	0.413	0.2585	Long-term series forecasting with Query Selector -- efficient model of sparse attention	-
DLinear	0.426	0.276	Are Transformers Effective for Time Series Forecasting?	-

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Time Series Forecasting On Etth2 720 2 | SOTA | HyperAI超神经