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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.

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  1. SolarBoost Public

    a boosting method for distributed photovoltaic power forecasting.

    Python 2 2

Repositories

Showing 10 of 19 repositories
  • XAI-for-Time-Series Public

    The official hub for our team dedicated to explainable AI (XAI) for time series, providing valuable resources to enhance understanding this critical field.

    3 MIT 0 0 0 Updated Apr 22, 2025
  • SolarBoost Public

    a boosting method for distributed photovoltaic power forecasting.

    Python 2 2 0 0 Updated Apr 15, 2025
  • WeatherODE Public

    The official code for "Mitigating Time Discretization Challenges with WeatherODE: A Sandwich Physics-Driven Neural ODE for Weather Forecasting".

    Python 12 1 1 0 Updated Oct 23, 2024
  • FusionSF Public
    Python 3 0 0 0 Updated Jun 13, 2024
  • NeurIPS2023-One-Fits-All Public

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

    Python 547 79 41 0 Updated Jan 8, 2024
  • ICDM2023-Tutorial-Time-Series Public

    ICDM’23 Tutorial, “Robust Time Series Analysis and Applications: A Interdisciplinary Approach”

    10 0 0 0 Updated Dec 3, 2023
  • Python 1 0 0 0 Updated Oct 13, 2023
  • Python 220 24 24 0 Updated Oct 9, 2023
  • KDD2022-Tutorial-Time-Series Public

    KDD'22 Tutorial: Robust Time Series Analysis and Applications An Industrial Perspective

    32 4 0 0 Updated Sep 22, 2023
  • .github Public
    0 0 0 0 Updated Aug 3, 2023

People

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