AI for Time Series
Volume 1: Unlocking Patterns with Deep Learning
$512.51
- Hardcover
252 pages
- Release Date
22 May 2026
Summary
This book provides a thorough exploration of the latest innovations in AI for general time series analysis, distribution shift, and foundation models. It offers an in-depth look at cutting-edge techniques and methodologies, using advanced algorithms that are transforming time series analysis across industries. The authors highlight the use of AI models, particularly those based on deep learning, to study the sequence of data points collected at successive points in time.
In the study …
Book Details
| ISBN-13: | 9781041010326 |
|---|---|
| ISBN-10: | 104101032X |
| Author: | Min Wu, Emadeldeen Eldele, Zhenghua Chen, Shirui Pan, Qingsong Wen, Xiaoli Li |
| Publisher: | Taylor & Francis Ltd |
| Imprint: | CRC Press |
| Format: | Hardcover |
| Number of Pages: | 252 |
| Release Date: | 22 May 2026 |
| Weight: | 0g |
| Dimensions: | 234mm x 156mm |
About The Author
Min Wu
Min Wu is currently a Principal Scientist at Institute for Infocomm Research (I2R), Agency for Science, Technology and Research (A*STAR), Singapore.
Emadeldeen Eldele is an Assistant Professor at Khalifa University, UAE.
Zhenghua Chen is a Senior Lecturer (Associate Professor) at University of Glasgow, UK.
Shirui Pan is a Professor and an ARC Future Fellow with the School of Information and Communication Technology, Griffith University, Australia.
Qingsong Wen is currently the Head of AI & Chief Scientist at Squirrel Ai Learning.
Xiaoli Li is currently Head of the Information Systems Technology and Design (ISTD) Pillar at Singapore University of Technology and Design (SUTD).
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