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RaptorMai/README.md

Hi there 👋

My name is Zheda(Marco) Mai, and I am a second-year Ph.D. student from the Department of Computer Science and Engineering at the Ohio State University, advised by Professor Wei-Lun (Harry) Chao. My research interests lie in continual learning, transfer learning and learning with limited & imperfect data.

I obtained my MASc. from the University of Toronto advised by Prof. Scott Sanner. I mostly worked on Continual Learning and Recommender Systems during my master collaborating with LG AI Research.

Prior to that, I completed my BASc. in Engineering Science at the University of Toronto, where I was fortunate to work with Dr. Erkang Zhu.

You can find more information about me at my personal page: https://zheda-mai.github.io/.

You can contact me at mai.145@osu.edu or by LinkedIn.

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  1. online-continual-learning online-continual-learning Public

    A collection of online continual learning paper implementations and tricks for computer vision in PyTorch, including our ASER(AAAI-21), SCR(CVPR21-W) and an online continual learning survey (Neuroc…

    Python 359 57

  2. CVPR20_CLVision_challenge CVPR20_CLVision_challenge Public

    1'st Place approach for CVPR 2020 Continual Learning Challenge

    Python 46 4

  3. Deep-AutoEncoder-Recommendation Deep-AutoEncoder-Recommendation Public

    Keras implementation of AutoRec and DeepRecommender from Nvidia.

    Jupyter Notebook 61 21

  4. xialeiliu/Awesome-Incremental-Learning xialeiliu/Awesome-Incremental-Learning Public

    Awesome Incremental Learning

    3.5k 549

  5. pgmpy-tutorial pgmpy-tutorial Public

    A pgmpy tutorial focus on Bayesian Model

    Jupyter Notebook 3 5

  6. bayesian-network-variable-elimination-gibbs-sampling bayesian-network-variable-elimination-gibbs-sampling Public

    Binary discrete variables bayesian network with variable elimination. It has the same interface as pgmpy

    Jupyter Notebook 4 1