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JohnGiorgi/README.md

Hi there πŸ‘‹

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I am a 4th-year computer science Ph.D. student at the University of Toronto and a graduate student researcher at the Donnelly Centre for Cellular and Biomolecular Research and the Vector Institute for Artificial Intelligence. I previously interned at Ai2 (on the Semantic Scholar team) and at Semantic Health. My work centres on natural language processing (NLP) and natural language understanding (NLU) of scientific text, particularly biomedical literature, but I am broadly interested in all things ML/AI/NLP. I completed an undergraduate degree at the University of Ottawa, graduating with a B.Sc in biochemistry. I completed an M.Sc. in computer science at the University of Toronto. When I am not πŸ’» I like to πŸš΅β€β™‚οΈ, πŸ‚ and πŸ‹οΈβ€β™‚οΈ.

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  1. DeCLUTR DeCLUTR Public

    The corresponding code from our paper "DeCLUTR: Deep Contrastive Learning for Unsupervised Textual Representations". Do not hesitate to open an issue if you run into any trouble!

    Python 378 33

  2. seq2rel seq2rel Public

    The corresponding code for our paper: A sequence-to-sequence approach for document-level relation extraction.

    Jupyter Notebook 60 8

  3. allenai/open-mds allenai/open-mds Public

    The corresponding code for our paper: "Exploring the Challenges of Open Domain Multi-Document Summarization". Do not hesitate to open an issue if you run into any trouble!

    Python 30 1

  4. BaderLab/Transfer-Learning-BNER-Bioinformatics-2018 BaderLab/Transfer-Learning-BNER-Bioinformatics-2018 Public

    This repository contains supplementary data, and links to the model and corpora used for the paper: Transfer learning for biomedical named entity recognition with neural networks.

    Python 36 6

  5. PathwayCommons/semantic-search PathwayCommons/semantic-search Public

    A simple semantic search engine for scientific papers.

    Python 27

  6. mathematics-for-machine-learning mathematics-for-machine-learning Public

    A set of notes, in the form of a simple Github Pages site, which will serve as a complete crash course on the various areas of mathematics essential to understanding machine learning.

    Jupyter Notebook 61 21