DAMO-DI-ML/AI-for-Time-Series-Papers-Tutorials-Surveys
📦 Open Source ProjectDAMO-DI-ML
A curated, comprehensive repository of top-tier research papers, tutorials, and surveys on AI for time series analysis.
The AI-for-Time-Series repository is an essential resource for anyone looking to master the intersection of artificial intelligence and temporal data analysis. It systematically categorizes state-of-the-art research, making it easier for developers and scientists to track advancements in time series forecasting, classification, and anomaly detection. The collection is meticulously curated to include publications from top-tier venues like NeurIPS, ICML, ICLR, KDD, and AAAI. Beyond just a list of papers, the repository includes surveys and tutorials that provide deep conceptual insights into complex architectures, including Transformers, RNNs, and Graph Neural Networks applied to time-dependent datasets. Whether you are building predictive maintenance systems, financial forecasting models, or spatio-temporal analysis tools, this repository offers the foundational literature required to understand current methodologies and future research directions in the field.
💡Highlights
- ├─Curated top-tier conference papers
- ├─Covers forecasting and anomaly detection
- └─Includes expert-led tutorials
🎯For
- ├─Data Scientists
- ├─AI Researchers
- └─Machine Learning Engineers