This repository is a curated list of papers, tutorials, and surveys on Artificial Intelligence for Time Series (AI4TS). It aims to provide researchers and engineers with a comprehensive and up-to-date resource covering various aspects of time series analysis, including forecasting, anomaly detection, classification, and imputation, across top AI conferences and journals.

How It Works

The repository systematically collects and categorizes AI4TS research papers, tutorials, and survey articles. It prioritizes inclusion from leading AI conferences (NeurIPS, ICML, ICLR, KDD, AAAI, IJCAI) and journals, ensuring coverage of state-of-the-art advancements. The list is updated promptly upon the announcement of accepted papers, making it a dynamic and timely resource.

Quick Start & Requirements

This repository is a curated list and does not require installation or execution. It serves as a reference guide to academic resources.

Highlighted Details

• Comprehensive coverage of AI4TS research from 2017 to the present.
• Includes papers with available code and links to official resources.
• Categorized by conference, year, and sub-task (forecasting, anomaly detection, etc.).
• Regularly updated with the latest accepted papers from top AI venues.

Maintenance & Community

The repository is maintained by qingsongedu and encourages community contributions through opening issues or pull requests for missed resources or errors.

Licensing & Compatibility

The repository itself is not software and does not have a license. The licenses of the individual papers referenced would vary.

Limitations & Caveats

This is a curated list of research papers and does not provide implementations or tools. Users must refer to the individual papers for their specific requirements and code availability.