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Foundation Models for Time Series Analysis: A Tutorial and Survey
March 25, 2024, 4:41 a.m. | Yuxuan Liang, Haomin Wen, Yuqi Nie, Yushan Jiang, Ming Jin, Dongjin Song, Shirui Pan, Qingsong Wen
cs.LG updates on arXiv.org arxiv.org
Abstract: Time series analysis stands as a focal point within the data mining community, serving as a cornerstone for extracting valuable insights crucial to a myriad of real-world applications. Recent advancements in Foundation Models (FMs) have fundamentally reshaped the paradigm of model design for time series analysis, boosting various downstream tasks in practice. These innovative approaches often leverage pre-trained or fine-tuned FMs to harness generalized knowledge tailored specifically for time series analysis. In this survey, we …
abstract analysis applications arxiv community cs.lg data data mining design foundation insights mining model design paradigm series survey time series tutorial type world
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