English(EN) In-Context Inpainting for Time Series Forecasting

ICI-Time框架将时间序列预测重构为视觉修复问题

作者 PulseAugur 编辑部 · [1 个来源] · 2026-08-24 21:57

研究人员开发了ICI-Time，一个将时间序列预测视为视觉修复问题的新框架。该方法通过将时间序列数据转换为面积图，然后用于模式补全任务，从而利用大型视觉模型。在流行病学、气象学和电力系统中的实验表明，ICI-Time在与现有深度学习方法相比时具有竞争力，尤其是在数据有限的情况下。 AI

影响这项研究引入了一个连接时间和视觉领域的新范式，可能为使用大型视觉模型进行时间序列预测提供新方法。

排序理由该条目描述了一个新颖的研究框架及其在科学论文中的应用。[lever_c_demoted from research: ic=1 ai=1.0]

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Hugging Face Daily Papers TIER_1 English(EN) · 2026-08-24 21:57

面向时间序列预测的上下文在绘

We propose ICI-Time, a novel framework that reframes time series forecasting as a visual inpainting task, leveraging the generalisation power of large vision models (LVMs). Unlike methods that require specialised temporal architectures and extensive domain-specific training, ICI-…