Machine learningTime-series forecasting
TimesFM：面向时间序列预测的仅解码器基础模型
TimesFM 是 Google 研究人员 Abhimanyu Das、Weihao Kong、Rajat Sen 和 Yichen Zhou 于 2024 年推出的一款用于单变量时间序列预测的预训练基础模型。该模型采用了类似大型语言模型的仅解码器 Transformer 架构，并在海量的真实世界和合成时间序列数据语料库上进行了训练。其核心创新在于能够在无需针对特定任务进行微调的情况下，跨不同领域实现准确的零样本预测。
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来源
- Das, A., Kong, W., Sen, R., & Zhou, Y. (2024). A decoder-only foundation model for time-series forecasting. ICML. link ↗
如何引用本页
ScholarGate. (2026, June 2). TimesFM (Time-series Foundation Model). ScholarGate. https://scholargate.app/zh/deep-learning/timesfm
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