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CM-BF/README.md

Howdy friends! πŸ‘‹

I'm glad to e-meet you here. My research interests span from computer vision, graph neural networks, to causality in machine learning and domain generalization. Hope you find my works interesting. I am enthusiastically open to collaboration and actively seeking internship opportunities. If you're interested in working together or have opportunities available, please feel free to reach out to me!

Recent works

🏠Personal Website |🎑Twitter |πŸ“²LinkedIn |πŸ”­Google Scholar

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  1. FeatureFlow FeatureFlow Public

    A state-of-the-art Video Frame Interpolation Method using feature flows blending. (CVPR 2020)

    Python 150 13

  2. divelab/DIG divelab/DIG Public

    A library for graph deep learning research

    Python 1.9k 284

  3. divelab/GOOD divelab/GOOD Public

    GOOD: A Graph Out-of-Distribution Benchmark [NeurIPS 2022 Datasets and Benchmarks]

    Python 187 19

  4. divelab/LECI divelab/LECI Public

    The implementation of "Joint Learning of Label and Environment Causal Independence for Graph Out-of-Distribution Generalization" (NeurIPS 2023)

    Python 18 1

  5. FlowX FlowX Public

    The official implementation of "FlowX: Towards Explainable Graph Neural Networks via Message Flows" [TPAMI 2023]

    Jupyter Notebook 5 1

  6. divelab/ATTA divelab/ATTA Public

    Active Test-Time Adaptation: Theoretical Analyses and An Algorithm [ICLR 2024]

    Python 17 2