{
  "id": 239673,
  "title": "ChemBERTa ",
  "url": "/competitions/bms-molecular-translation/discussion/239673",
  "author_name": "",
  "post_date": "2021-05-17T09:07:46.600409300Z",
  "votes": null,
  "comment_count": 1,
  "views": 0,
  "content": "<h2>YouTube: <a href=\"https://www.youtube.com/watch?v=b3AMBZsgvug\" target=\"_blank\">https://www.youtube.com/watch?v=b3AMBZsgvug</a></h2>\n<hr>\n<p>ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction by Seyone Chithrananda, Gabe Grand, Elana Simon, Walid Ahmed, and Bharath Ramsundar (ArXiv: <a href=\"https://arxiv.org/abs/2010.09885​\" target=\"_blank\">https://arxiv.org/abs/2010.09885​</a>)</p>\n<p>Presented at Scientific Machine Learning Webinar Series at Carnegie Mellon University, Feb 18, 2021 (<a href=\"https://www.cmu.edu/aced/sciML.html​)\" target=\"_blank\">https://www.cmu.edu/aced/sciML.html​)</a>.</p>\n<p>Organized by Dilip Krishnamurthy and Venkat Viswanathan<br>\nChair: Tom Miller, Caltech and Entos, Inc</p>\n<p>NeurIPS ML for Molecules Paper: <a href=\"https://ml4molecules.github.io/papers…\" target=\"_blank\">https://ml4molecules.github.io/papers…</a><br>\nGitHub: <a href=\"https://github.com/seyonechithrananda…\" target=\"_blank\">https://github.com/seyonechithrananda…</a><br>\nTutorial: <a href=\"https://github.com/deepchem/deepchem/…\" target=\"_blank\">https://github.com/deepchem/deepchem/…</a><br>\nDeepChem: <a href=\"https://deepchem.io/\" target=\"_blank\">https://deepchem.io/</a></p>",
  "messages": [
    {
      "id": "1311248",
      "postDate": "05/17/2021 09:07:46",
      "content": "<h2>YouTube: <a href=\"https://www.youtube.com/watch?v=b3AMBZsgvug\" target=\"_blank\">https://www.youtube.com/watch?v=b3AMBZsgvug</a></h2>\n<hr>\n<p>ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction by Seyone Chithrananda, Gabe Grand, Elana Simon, Walid Ahmed, and Bharath Ramsundar (ArXiv: <a href=\"https://arxiv.org/abs/2010.09885​\" target=\"_blank\">https://arxiv.org/abs/2010.09885​</a>)</p>\n<p>Presented at Scientific Machine Learning Webinar Series at Carnegie Mellon University, Feb 18, 2021 (<a href=\"https://www.cmu.edu/aced/sciML.html​)\" target=\"_blank\">https://www.cmu.edu/aced/sciML.html​)</a>.</p>\n<p>Organized by Dilip Krishnamurthy and Venkat Viswanathan<br>\nChair: Tom Miller, Caltech and Entos, Inc</p>\n<p>NeurIPS ML for Molecules Paper: <a href=\"https://ml4molecules.github.io/papers…\" target=\"_blank\">https://ml4molecules.github.io/papers…</a><br>\nGitHub: <a href=\"https://github.com/seyonechithrananda…\" target=\"_blank\">https://github.com/seyonechithrananda…</a><br>\nTutorial: <a href=\"https://github.com/deepchem/deepchem/…\" target=\"_blank\">https://github.com/deepchem/deepchem/…</a><br>\nDeepChem: <a href=\"https://deepchem.io/\" target=\"_blank\">https://deepchem.io/</a></p>",
      "rawMarkdown": "## YouTube: https://www.youtube.com/watch?v=b3AMBZsgvug\n\n----\n\nChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction by Seyone Chithrananda, Gabe Grand, Elana Simon, Walid Ahmed, and Bharath Ramsundar (ArXiv: https://arxiv.org/abs/2010.09885​)\n\nPresented at Scientific Machine Learning Webinar Series at Carnegie Mellon University, Feb 18, 2021 (https://www.cmu.edu/aced/sciML.html​).\n\nOrganized by Dilip Krishnamurthy and Venkat Viswanathan\nChair: Tom Miller, Caltech and Entos, Inc\n\nNeurIPS ML for Molecules Paper: https://ml4molecules.github.io/papers...\nGitHub: https://github.com/seyonechithrananda...\nTutorial: https://github.com/deepchem/deepchem/...\nDeepChem: https://deepchem.io/",
      "votes": null
    },
    {
      "id": "1312794",
      "postDate": "05/18/2021 08:52:45",
      "content": "<p>Thank you for sharing. I met some mentions of ChemBERTa and had just thought about it. How do you think what is the best way to use it in this project? </p>",
      "rawMarkdown": "Thank you for sharing. I met some mentions of ChemBERTa and had just thought about it. How do you think what is the best way to use it in this project?",
      "votes": null
    }
  ],
  "comments": [
    {
      "id": 1312794,
      "author_name": "kseniapolonskaya",
      "author_url": "",
      "post_date": "05/18/2021 08:52:45",
      "content": "<p>Thank you for sharing. I met some mentions of ChemBERTa and had just thought about it. How do you think what is the best way to use it in this project? </p>",
      "votes": null,
      "replies": []
    }
  ],
  "raw_markdown_by_id": {
    "1311248": "## YouTube: https://www.youtube.com/watch?v=b3AMBZsgvug\n\n----\n\nChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction by Seyone Chithrananda, Gabe Grand, Elana Simon, Walid Ahmed, and Bharath Ramsundar (ArXiv: https://arxiv.org/abs/2010.09885​)\n\nPresented at Scientific Machine Learning Webinar Series at Carnegie Mellon University, Feb 18, 2021 (https://www.cmu.edu/aced/sciML.html​).\n\nOrganized by Dilip Krishnamurthy and Venkat Viswanathan\nChair: Tom Miller, Caltech and Entos, Inc\n\nNeurIPS ML for Molecules Paper: https://ml4molecules.github.io/papers...\nGitHub: https://github.com/seyonechithrananda...\nTutorial: https://github.com/deepchem/deepchem/...\nDeepChem: https://deepchem.io/",
    "1312794": "Thank you for sharing. I met some mentions of ChemBERTa and had just thought about it. How do you think what is the best way to use it in this project?"
  },
  "source": "meta"
}