{
  "id": 379675,
  "title": "Arxiv paper about core of task",
  "url": "/competitions/icecube-neutrinos-in-deep-ice/discussion/379675",
  "author_name": "Mike Mazurov",
  "post_date": "2023-01-20T15:38:50.039000",
  "votes": 11,
  "comment_count": 4,
  "views": 0,
  "content": "<h2>This paper seems like very relevant to task:</h2>\n<h4>\"Deep-learning-based reconstruction of the neutrino direction and energy for in-ice radio detectors\"</h4>\n<h4><a href=\"https://arxiv.org/pdf/2205.15872.pdf\" target=\"_blank\">https://arxiv.org/pdf/2205.15872.pdf</a></h4>",
  "messages": [
    {
      "id": 2108518,
      "postDate": "2023-01-20T15:38:50.040Z",
      "content": "<h2>This paper seems like very relevant to task:</h2>\n<h4>\"Deep-learning-based reconstruction of the neutrino direction and energy for in-ice radio detectors\"</h4>\n<h4><a href=\"https://arxiv.org/pdf/2205.15872.pdf\" target=\"_blank\">https://arxiv.org/pdf/2205.15872.pdf</a></h4>",
      "rawMarkdown": "## This paper seems like very relevant to task: \n#### \"Deep-learning-based reconstruction of the neutrino direction and energy for in-ice radio detectors\"\n#### https://arxiv.org/pdf/2205.15872.pdf",
      "votes": 11
    },
    {
      "id": 2109738,
      "postDate": "2023-01-21T16:06:00.710Z",
      "content": "<p>Great paper <a href=\"https://www.kaggle.com/mikhailma\" target=\"_blank\">@mikhailma</a>! For anyone curious, the paper discusses the use for a deep neural network to predict ultra-high-energy (UHE) neutrinos. The DNN predicts the energy and a standard deviation of a factor of two around the true energy. This could be a useful paper.</p>",
      "rawMarkdown": "Great paper @mikhailma! For anyone curious, the paper discusses the use for a deep neural network to predict ultra-high-energy (UHE) neutrinos. The DNN predicts the energy and a standard deviation of a factor of two around the true energy. This could be a useful paper.",
      "votes": 1
    },
    {
      "id": 2108591,
      "postDate": "2023-01-20T16:46:17.093Z",
      "content": "<p>It seems to me that it is a different detector technology (radio detectors vs digital optical modules). Still very relevant!</p>",
      "rawMarkdown": "It seems to me that it is a different detector technology (radio detectors vs digital optical modules). Still very relevant!",
      "votes": 2
    },
    {
      "id": 2111483,
      "postDate": "2023-01-22T23:21:08.617Z",
      "content": "<p>Cool paper, thank you for sharing.</p>\n<p>The Devastator.</p>",
      "rawMarkdown": "Cool paper, thank you for sharing.\n\nThe Devastator.\n"
    },
    {
      "id": 2118110,
      "postDate": "2023-01-27T19:20:09.657Z",
      "rawMarkdown": "",
      "isDeleted": true
    }
  ],
  "comments": [
    {
      "id": 2109738,
      "author_name": "Ravi Shah",
      "author_url": "",
      "post_date": "2023-01-21T16:06:00.710000",
      "content": "<p>Great paper <a href=\"https://www.kaggle.com/mikhailma\" target=\"_blank\">@mikhailma</a>! For anyone curious, the paper discusses the use for a deep neural network to predict ultra-high-energy (UHE) neutrinos. The DNN predicts the energy and a standard deviation of a factor of two around the true energy. This could be a useful paper.</p>",
      "votes": 1,
      "replies": []
    },
    {
      "id": 2108591,
      "author_name": "Jean-Loup Tastet",
      "author_url": "",
      "post_date": "2023-01-20T16:46:17.093000",
      "content": "<p>It seems to me that it is a different detector technology (radio detectors vs digital optical modules). Still very relevant!</p>",
      "votes": 2,
      "replies": []
    },
    {
      "id": 2111483,
      "author_name": "The Devastator",
      "author_url": "",
      "post_date": "2023-01-22T23:21:08.617000",
      "content": "<p>Cool paper, thank you for sharing.</p>\n<p>The Devastator.</p>",
      "votes": 0,
      "replies": []
    },
    {
      "id": 2118110,
      "author_name": "",
      "author_url": "",
      "post_date": "2023-01-27T19:20:09.657000",
      "content": "",
      "votes": 0,
      "replies": []
    }
  ],
  "raw_markdown_by_id": {
    "2108518": "## This paper seems like very relevant to task: \n#### \"Deep-learning-based reconstruction of the neutrino direction and energy for in-ice radio detectors\"\n#### https://arxiv.org/pdf/2205.15872.pdf",
    "2109738": "Great paper @mikhailma! For anyone curious, the paper discusses the use for a deep neural network to predict ultra-high-energy (UHE) neutrinos. The DNN predicts the energy and a standard deviation of a factor of two around the true energy. This could be a useful paper.",
    "2108591": "It seems to me that it is a different detector technology (radio detectors vs digital optical modules). Still very relevant!",
    "2111483": "Cool paper, thank you for sharing.\n\nThe Devastator.\n",
    "2118110": ""
  }
}