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@DAMO-DI-ML

DAMO-DI-ML

AI for Time Series (AI4TS) and XAI

We are a group of engineers and researchers from the Decision Intelligence Lab of DAMO Academy, Alibaba Group, led by Dr. Liang Sun. Motivated by challenging problems arising from industry, we are working on AI for time series and explainable AI (XAI), including time series anomaly detection, time series forecasting, rule learning, and effective and efficient explaining methods for time series.

Our team is located in Hangzhou, China and Bellevue, WA, USA. We are very happy to hire interns in both Hangzhou and Bellevue for collaboration on cutting-edge research on time series and XAI. For internship opportunity, please contact liang[dot]sun[at]alibaba-inc.com.

More introduction to our lab - Decision Intelligence Lab, please go to our official website.

Popular repositories

  1. NeurIPS2023-One-Fits-All NeurIPS2023-One-Fits-All Public

    The official code for "One Fits All: Power General Time Series Analysis by Pretrained LM (NeurIPS 2023 Spotlight)"

    Python 368 54

  2. ICML2022-FEDformer ICML2022-FEDformer Public

    Source code of ICML'22 paper: FEDformer: Frequency Enhanced Decomposed Transformer for Long-term Series Forecasting

    Python 186 30

  3. KDD2023-DCdetector KDD2023-DCdetector Public

    Python 149 15

  4. AI-for-Time-Series-Papers-Tutorials-Surveys AI-for-Time-Series-Papers-Tutorials-Surveys Public

    A professional list of Papers, Tutorials, and Surveys on AI for Time Series in top AI conferences and journals.

    144 26

  5. CIKM22-TFAD CIKM22-TFAD Public

    Source code of CIKM'22 paper: TFAD: A Decomposition Time Series Anomaly Detection Architecture with Frequency Analysis

    Python 44 9

  6. AAAI2022-HCM AAAI2022-HCM Public

    Source code of AAAI'22 paper: A Hybrid Causal Structure Learning Algorithm for Mixed-type Data

    Python 36 5

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