{
  "id": 104198,
  "title": "Kernels having under 40 PublicLB Score",
  "url": "/competitions/generative-dog-images/discussion/104198",
  "author_name": "",
  "post_date": "2019-08-15T06:04:54.118709200Z",
  "votes": 11,
  "comment_count": 2,
  "views": 0,
  "content": "<p>Thanks for your sharing!!!!\nbestfitting[12.46326] [ <a href=\"https://www.kaggle.com/bestfitting/i96-1e-4-6e-4-bs32-195\">https://www.kaggle.com/bestfitting/i96-1e-4-6e-4-bs32-195</a> ]\nbestfitting[13.44647] [ <a href=\"https://www.kaggle.com/bestfitting/i96-crop-mode3-dstep1-1e-4-6e-4-bs32\">https://www.kaggle.com/bestfitting/i96-crop-mode3-dstep1-1e-4-6e-4-bs32</a> ]</p>\n\n<p>Dmitry Vorobiev[14.95516] [ <a href=\"https://www.kaggle.com/dvorobiev/doggies-biggan-sub-data-aug-3\">https://www.kaggle.com/dvorobiev/doggies-biggan-sub-data-aug-3</a> ]</p>\n\n<p>yabea [15.81605] [ <a href=\"https://www.kaggle.com/yukia18/sub-rals-ac-biggan-with-minibatchstddev?scriptVersionId=18828724\">https://www.kaggle.com/yukia18/sub-rals-ac-biggan-with-minibatchstddev?scriptVersionId=18828724</a> ]</p>\n\n<p>Theo Viel [30.33340] [ <a href=\"https://www.kaggle.com/theoviel/conditional-progan-30-public?scriptVersionId=18873238\">https://www.kaggle.com/theoviel/conditional-progan-30-public?scriptVersionId=18873238</a> ]</p>\n\n<p>Alvaro[30.65492] [ <a href=\"https://www.kaggle.com/alvaroma/dcgan-lb-30-65\">https://www.kaggle.com/alvaroma/dcgan-lb-30-65</a> ]</p>\n\n<p>Naomichi Agata [36.76123] [ <a href=\"https://www.kaggle.com/agatan/sagan-resnet-annots?scriptVersionId=16816757\">https://www.kaggle.com/agatan/sagan-resnet-annots?scriptVersionId=16816757</a> ]</p>\n\n<p>Johannl[38.26191]  [ <a href=\"https://www.kaggle.com/johannl/sn-dcgan-style?scriptVersionId=18780768\">https://www.kaggle.com/johannl/sn-dcgan-style?scriptVersionId=18780768</a> ]</p>\n\n<p>Happy GAN[38.70295] [ <a href=\"https://www.kaggle.com/leonshangguan/dcgan-data-cleaning-sub-v1?scriptVersionId=18470145\">https://www.kaggle.com/leonshangguan/dcgan-data-cleaning-sub-v1?scriptVersionId=18470145</a> ]</p>\n\n<p>hirune924[38.92350] [ <a href=\"https://www.kaggle.com/hirune924/public-lb-38-92350-solution\">https://www.kaggle.com/hirune924/public-lb-38-92350-solution</a> ]</p>",
  "messages": [
    {
      "id": "599563",
      "postDate": "08/15/2019 06:04:54",
      "content": "<p>Thanks for your sharing!!!!\nbestfitting[12.46326] [ <a href=\"https://www.kaggle.com/bestfitting/i96-1e-4-6e-4-bs32-195\">https://www.kaggle.com/bestfitting/i96-1e-4-6e-4-bs32-195</a> ]\nbestfitting[13.44647] [ <a href=\"https://www.kaggle.com/bestfitting/i96-crop-mode3-dstep1-1e-4-6e-4-bs32\">https://www.kaggle.com/bestfitting/i96-crop-mode3-dstep1-1e-4-6e-4-bs32</a> ]</p>\n\n<p>Dmitry Vorobiev[14.95516] [ <a href=\"https://www.kaggle.com/dvorobiev/doggies-biggan-sub-data-aug-3\">https://www.kaggle.com/dvorobiev/doggies-biggan-sub-data-aug-3</a> ]</p>\n\n<p>yabea [15.81605] [ <a href=\"https://www.kaggle.com/yukia18/sub-rals-ac-biggan-with-minibatchstddev?scriptVersionId=18828724\">https://www.kaggle.com/yukia18/sub-rals-ac-biggan-with-minibatchstddev?scriptVersionId=18828724</a> ]</p>\n\n<p>Theo Viel [30.33340] [ <a href=\"https://www.kaggle.com/theoviel/conditional-progan-30-public?scriptVersionId=18873238\">https://www.kaggle.com/theoviel/conditional-progan-30-public?scriptVersionId=18873238</a> ]</p>\n\n<p>Alvaro[30.65492] [ <a href=\"https://www.kaggle.com/alvaroma/dcgan-lb-30-65\">https://www.kaggle.com/alvaroma/dcgan-lb-30-65</a> ]</p>\n\n<p>Naomichi Agata [36.76123] [ <a href=\"https://www.kaggle.com/agatan/sagan-resnet-annots?scriptVersionId=16816757\">https://www.kaggle.com/agatan/sagan-resnet-annots?scriptVersionId=16816757</a> ]</p>\n\n<p>Johannl[38.26191]  [ <a href=\"https://www.kaggle.com/johannl/sn-dcgan-style?scriptVersionId=18780768\">https://www.kaggle.com/johannl/sn-dcgan-style?scriptVersionId=18780768</a> ]</p>\n\n<p>Happy GAN[38.70295] [ <a href=\"https://www.kaggle.com/leonshangguan/dcgan-data-cleaning-sub-v1?scriptVersionId=18470145\">https://www.kaggle.com/leonshangguan/dcgan-data-cleaning-sub-v1?scriptVersionId=18470145</a> ]</p>\n\n<p>hirune924[38.92350] [ <a href=\"https://www.kaggle.com/hirune924/public-lb-38-92350-solution\">https://www.kaggle.com/hirune924/public-lb-38-92350-solution</a> ]</p>",
      "rawMarkdown": "Thanks for your sharing!!!!\nbestfitting[12.46326] [ https://www.kaggle.com/bestfitting/i96-1e-4-6e-4-bs32-195 ]\nbestfitting[13.44647] [ https://www.kaggle.com/bestfitting/i96-crop-mode3-dstep1-1e-4-6e-4-bs32 ]\n\nDmitry Vorobiev[14.95516] [ https://www.kaggle.com/dvorobiev/doggies-biggan-sub-data-aug-3 ]\n\nyabea [15.81605] [ https://www.kaggle.com/yukia18/sub-rals-ac-biggan-with-minibatchstddev?scriptVersionId=18828724 ]\n\nTheo Viel [30.33340] [ https://www.kaggle.com/theoviel/conditional-progan-30-public?scriptVersionId=18873238 ]\n\nAlvaro[30.65492] [ https://www.kaggle.com/alvaroma/dcgan-lb-30-65 ]\n\nNaomichi Agata [36.76123] [ https://www.kaggle.com/agatan/sagan-resnet-annots?scriptVersionId=16816757 ]\n\nJohannl[38.26191]  [ https://www.kaggle.com/johannl/sn-dcgan-style?scriptVersionId=18780768 ]\n\nHappy GAN[38.70295] [ https://www.kaggle.com/leonshangguan/dcgan-data-cleaning-sub-v1?scriptVersionId=18470145 ]\n\nhirune924[38.92350] [ https://www.kaggle.com/hirune924/public-lb-38-92350-solution ]",
      "votes": null
    },
    {
      "id": "599915",
      "postDate": "08/15/2019 12:56:05",
      "content": "<p>thanks for sharing.</p>",
      "rawMarkdown": "thanks for sharing.",
      "votes": null
    },
    {
      "id": "601235",
      "postDate": "08/17/2019 08:31:02",
      "content": "<p>Thank you for sharing!</p>",
      "rawMarkdown": "Thank you for sharing!",
      "votes": null
    }
  ],
  "comments": [
    {
      "id": 599915,
      "author_name": "fajsoe",
      "author_url": "",
      "post_date": "08/15/2019 12:56:05",
      "content": "<p>thanks for sharing.</p>",
      "votes": null,
      "replies": []
    },
    {
      "id": 601235,
      "author_name": "darbin",
      "author_url": "",
      "post_date": "08/17/2019 08:31:02",
      "content": "<p>Thank you for sharing!</p>",
      "votes": null,
      "replies": []
    }
  ],
  "raw_markdown_by_id": {
    "599563": "Thanks for your sharing!!!!\nbestfitting[12.46326] [ https://www.kaggle.com/bestfitting/i96-1e-4-6e-4-bs32-195 ]\nbestfitting[13.44647] [ https://www.kaggle.com/bestfitting/i96-crop-mode3-dstep1-1e-4-6e-4-bs32 ]\n\nDmitry Vorobiev[14.95516] [ https://www.kaggle.com/dvorobiev/doggies-biggan-sub-data-aug-3 ]\n\nyabea [15.81605] [ https://www.kaggle.com/yukia18/sub-rals-ac-biggan-with-minibatchstddev?scriptVersionId=18828724 ]\n\nTheo Viel [30.33340] [ https://www.kaggle.com/theoviel/conditional-progan-30-public?scriptVersionId=18873238 ]\n\nAlvaro[30.65492] [ https://www.kaggle.com/alvaroma/dcgan-lb-30-65 ]\n\nNaomichi Agata [36.76123] [ https://www.kaggle.com/agatan/sagan-resnet-annots?scriptVersionId=16816757 ]\n\nJohannl[38.26191]  [ https://www.kaggle.com/johannl/sn-dcgan-style?scriptVersionId=18780768 ]\n\nHappy GAN[38.70295] [ https://www.kaggle.com/leonshangguan/dcgan-data-cleaning-sub-v1?scriptVersionId=18470145 ]\n\nhirune924[38.92350] [ https://www.kaggle.com/hirune924/public-lb-38-92350-solution ]",
    "599915": "thanks for sharing.",
    "601235": "Thank you for sharing!"
  },
  "source": "meta"
}