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One Fits All: Universal Time Series Analysis by Pretrained LM and
  Specially Designed Adaptors

One Fits All: Universal Time Series Analysis by Pretrained LM and Specially Designed Adaptors

24 November 2023
Tian Zhou
Peisong Niu
Xue Wang
Liang Sun
Rong Jin
    AI4TS
ArXivPDFHTML

Papers citing "One Fits All: Universal Time Series Analysis by Pretrained LM and Specially Designed Adaptors"

4 / 4 papers shown
Title
DCdetector: Dual Attention Contrastive Representation Learning for Time
  Series Anomaly Detection
DCdetector: Dual Attention Contrastive Representation Learning for Time Series Anomaly Detection
Yiyuan Yang
Chaoli Zhang
Tian Zhou
Qingsong Wen
Liang Sun
AI4TS
54
28
0
17 Jun 2023
In-context Learning and Induction Heads
In-context Learning and Induction Heads
Catherine Olsson
Nelson Elhage
Neel Nanda
Nicholas Joseph
Nova Dassarma
...
Tom B. Brown
Jack Clark
Jared Kaplan
Sam McCandlish
C. Olah
203
326
0
24 Sep 2022
Informer: Beyond Efficient Transformer for Long Sequence Time-Series
  Forecasting
Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting
Haoyi Zhou
Shanghang Zhang
J. Peng
Shuai Zhang
Jianxin Li
Hui Xiong
Wan Zhang
AI4TS
127
2,327
0
14 Dec 2020
A simpler approach to obtaining an O(1/t) convergence rate for the
  projected stochastic subgradient method
A simpler approach to obtaining an O(1/t) convergence rate for the projected stochastic subgradient method
Simon Lacoste-Julien
Mark W. Schmidt
Francis R. Bach
99
253
0
10 Dec 2012
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