Machine learningTime-series forecasting
TiDE：时间序列密集编码器
TiDE（时间序列密集编码器）是一种基于MLP的编码器-解码器架构，用于长期多元时间序列预测，由Google Research的Abhimanyu Das及其同事于2023年提出。该模型通过堆叠的密集（MLP）层对过去的时序列观测以及静态和动态协变量进行编码，然后将潜在表示解码为未来的预测。TiDE表明，在标准的长期预测基准上，简单的线性和密集架构可以媲美甚至超越基于Transformer的模型，同时速度显著更快。
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来源
- Das, A., Kong, W., Leach, A., Mathur, S., Sen, R., & Yu, R. (2023). Long-term forecasting with TiDE: Time-series dense encoder. Transactions on Machine Learning Research. link ↗
如何引用本页
ScholarGate. (2026, June 2). TiDE (Time-series Dense Encoder). ScholarGate. https://scholargate.app/zh/deep-learning/tide
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