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20232026
most citedFoundation Models for Time Series Analysis: A Tutorial and Survey

221 citations · 250 across the 11 of their papers we have counts for

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Showing 2024Show all

5 papers · 1 filter

cs.LG2024

Learning System Dynamics without Forgetting

Xikun Zhang, Dongjin Song, Yushan Jiang +2

Observation-based trajectory prediction for systems with unknown dynamics is essential in fields such as physics and biology. Most existing approaches are limited to learning withi…

cs.LG2024★ 221 cited

Foundation Models for Time Series Analysis: A Tutorial and Survey

Yuxuan Liang, Haomin Wen, Yuqi Nie +5

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 applicati…

cs.LG2024★ 1 cited

IP-LLM: Semantic Space Informed Prompt Learning with LLM for Time Series Forecasting

Zijie Pan, Yushan Jiang, Sahil Garg +3

Recently, there has been a growing interest in leveraging pre-trained large language models (LLMs) for various time series applications. However, the semantic space of LLMs, establ…

cs.LG2024

Structural Knowledge Informed Continual Multivariate Time Series Forecasting

Zijie Pan, Yushan Jiang, Dongjin Song +4

Recent studies in multivariate time series (MTS) forecasting reveal that explicitly modeling the hidden dependencies among different time series can yield promising forecasting per…

cs.LG2024★ 3 cited

Empowering Time Series Analysis with Large Language Models: A Survey

Yushan Jiang, Zijie Pan, Xikun Zhang +4

Recently, remarkable progress has been made over large language models (LLMs), demonstrating their unprecedented capability in varieties of natural language tasks. However, complet…