{ "id": 275426, "title": "Top solutions collection", "url": "/competitions/g2net-gravitational-wave-detection/discussion/275426", "author_name": "", "post_date": "2021-09-30T11:19:18.457359400Z", "votes": 15, "comment_count": 5, "views": 0, "content": "

A collection of the top shared solutions' discussion, I will update once we get more.

\n

Money 🔥 solutions:

\n\n

Gold ☀️ solutions

\n\n

Silver ✨ solutions

\n\n

I will try to share some of the major insights of what worked.

\n

Some insights of what worked well:

\n", "messages": [ { "id": "1529408", "postDate": "09/30/2021 11:19:18", "content": "

A collection of the top shared solutions' discussion, I will update once we get more.

\n

Money 🔥 solutions:

\n\n

Gold ☀️ solutions

\n\n

Silver ✨ solutions

\n\n

I will try to share some of the major insights of what worked.

\n

Some insights of what worked well:

\n", "rawMarkdown": "A collection of the top shared solutions' discussion, I will update once we get more. \n\nMoney 🔥 solutions: \n\n- **1st place**: [DSP](https://www.kaggle.com/c/g2net-gravitational-wave-detection/discussion/275507) and [deep learning](https://www.kaggle.com/c/g2net-gravitational-wave-detection/discussion/275476).\n- 2nd [place](https://www.kaggle.com/c/g2net-gravitational-wave-detection/discussion/275341) \n- 3rd [place](https://www.kaggle.com/c/g2net-gravitational-wave-detection/discussion/275617) and source [code](https://github.com/VincentWang25/G2Net_GoGoGo)\n\nGold ☀️ solutions\n\n- 4th [place](https://www.kaggle.com/c/g2net-gravitational-wave-detection/discussion/275331) \n- 5th [place]( https://www.kaggle.com/c/g2net-gravitational-wave-detection/discussion/275334)\n- 6th [place](https://www.kaggle.com/c/g2net-gravitational-wave-detection/discussion/275343)\n- 7th [place](https://www.kaggle.com/c/g2net-gravitational-wave-detection/discussion/275349)\n- 8th place [augmentation](https://www.kaggle.com/c/g2net-gravitational-wave-detection/discussion/275335) and [more general](https://www.kaggle.com/c/g2net-gravitational-wave-detection/discussion/275433)\n- 10th [place](https://www.kaggle.com/c/g2net-gravitational-wave-detection/discussion/275353) \n- 11th [place]( https://www.kaggle.com/c/g2net-gravitational-wave-detection/discussion/275405)\n- 12th [place](https://www.kaggle.com/c/g2net-gravitational-wave-detection/discussion/275356) \n\nSilver ✨ solutions\n\n- 13th [place](https://www.kaggle.com/c/g2net-gravitational-wave-detection/discussion/275841)\n- 15th [place](https://www.kaggle.com/c/g2net-gravitational-wave-detection/discussion/275431)\n- 18th [place](https://www.kaggle.com/c/g2net-gravitational-wave-detection/discussion/275318)\n- 23rd [place](https://www.kaggle.com/c/g2net-gravitational-wave-detection/discussion/275728)\n- 57th [place](https://www.kaggle.com/c/g2net-gravitational-wave-detection/discussion/275360)\n\n\nI will try to share some of the major insights of what worked.\n\n\nSome insights of what worked well:\n\n- Models using [Conv1D](https://pytorch.org/docs/stable/generated/torch.nn.Conv1d.html) and raw signal\n- Channel shuffling as an augmentation technique", "votes": null }, { "id": "1530798", "postDate": "10/01/2021 12:46:06", "content": "

Thanks for this collection of shared solution.
\nMerci! Have a nice day :)

", "rawMarkdown": "Thanks for this collection of shared solution. \nMerci! Have a nice day :)", "votes": null }, { "id": "1531087", "postDate": "10/01/2021 15:56:23", "content": "

I am glad it helps, let me know if you learn something new. :)

", "rawMarkdown": "I am glad it helps, let me know if you learn something new. :)", "votes": null }, { "id": "1532718", "postDate": "10/03/2021 10:00:31", "content": "

Amazing work. thank u for collect these good places.

", "rawMarkdown": "Amazing work. thank u for collect these good places.", "votes": null }, { "id": "1532762", "postDate": "10/03/2021 11:10:22", "content": "

Thanks and most importantly thanks to those that made these write-ups and solutions.

", "rawMarkdown": "Thanks and most importantly thanks to those that made these write-ups and solutions.", "votes": null }, { "id": "1559905", "postDate": "10/27/2021 08:07:43", "content": "

Hey All,

\n

Thank you all for taking part in our competition. The participation has been overwhelmingly positive. We are currently conducting a survey to gauge the demographic and outreach achieved. Kindly spare 2min and fill in this survey https://forms.gle/QP9L16niPexozyhu5.

\n

Thank you all,

\n

Regards,
\nChris

", "rawMarkdown": "Hey All,\n\nThank you all for taking part in our competition. The participation has been overwhelmingly positive. We are currently conducting a survey to gauge the demographic and outreach achieved. Kindly spare 2min and fill in this survey https://forms.gle/QP9L16niPexozyhu5.\n\nThank you all,\n\nRegards,\nChris", "votes": null } ], "comments": [ { "id": 1530798, "author_name": "matthirou", "author_url": "", "post_date": "10/01/2021 12:46:06", "content": "

Thanks for this collection of shared solution.
\nMerci! Have a nice day :)

", "votes": null, "replies": [ { "id": 1531087, "author_name": "yassinealouini", "author_url": "", "post_date": "10/01/2021 15:56:23", "content": "

I am glad it helps, let me know if you learn something new. :)

", "votes": null, "replies": [] } ] }, { "id": 1532718, "author_name": "mohamedbakrey", "author_url": "", "post_date": "10/03/2021 10:00:31", "content": "

Amazing work. thank u for collect these good places.

", "votes": null, "replies": [ { "id": 1532762, "author_name": "yassinealouini", "author_url": "", "post_date": "10/03/2021 11:10:22", "content": "

Thanks and most importantly thanks to those that made these write-ups and solutions.

", "votes": null, "replies": [] } ] }, { "id": 1559905, "author_name": "zerafachris", "author_url": "", "post_date": "10/27/2021 08:07:43", "content": "

Hey All,

\n

Thank you all for taking part in our competition. The participation has been overwhelmingly positive. We are currently conducting a survey to gauge the demographic and outreach achieved. Kindly spare 2min and fill in this survey https://forms.gle/QP9L16niPexozyhu5.

\n

Thank you all,

\n

Regards,
\nChris

", "votes": null, "replies": [] } ], "raw_markdown_by_id": { "1529408": "A collection of the top shared solutions' discussion, I will update once we get more. \n\nMoney 🔥 solutions: \n\n- **1st place**: [DSP](https://www.kaggle.com/c/g2net-gravitational-wave-detection/discussion/275507) and [deep learning](https://www.kaggle.com/c/g2net-gravitational-wave-detection/discussion/275476).\n- 2nd [place](https://www.kaggle.com/c/g2net-gravitational-wave-detection/discussion/275341) \n- 3rd [place](https://www.kaggle.com/c/g2net-gravitational-wave-detection/discussion/275617) and source [code](https://github.com/VincentWang25/G2Net_GoGoGo)\n\nGold ☀️ solutions\n\n- 4th [place](https://www.kaggle.com/c/g2net-gravitational-wave-detection/discussion/275331) \n- 5th [place]( https://www.kaggle.com/c/g2net-gravitational-wave-detection/discussion/275334)\n- 6th [place](https://www.kaggle.com/c/g2net-gravitational-wave-detection/discussion/275343)\n- 7th [place](https://www.kaggle.com/c/g2net-gravitational-wave-detection/discussion/275349)\n- 8th place [augmentation](https://www.kaggle.com/c/g2net-gravitational-wave-detection/discussion/275335) and [more general](https://www.kaggle.com/c/g2net-gravitational-wave-detection/discussion/275433)\n- 10th [place](https://www.kaggle.com/c/g2net-gravitational-wave-detection/discussion/275353) \n- 11th [place]( https://www.kaggle.com/c/g2net-gravitational-wave-detection/discussion/275405)\n- 12th [place](https://www.kaggle.com/c/g2net-gravitational-wave-detection/discussion/275356) \n\nSilver ✨ solutions\n\n- 13th [place](https://www.kaggle.com/c/g2net-gravitational-wave-detection/discussion/275841)\n- 15th [place](https://www.kaggle.com/c/g2net-gravitational-wave-detection/discussion/275431)\n- 18th [place](https://www.kaggle.com/c/g2net-gravitational-wave-detection/discussion/275318)\n- 23rd [place](https://www.kaggle.com/c/g2net-gravitational-wave-detection/discussion/275728)\n- 57th [place](https://www.kaggle.com/c/g2net-gravitational-wave-detection/discussion/275360)\n\n\nI will try to share some of the major insights of what worked.\n\n\nSome insights of what worked well:\n\n- Models using [Conv1D](https://pytorch.org/docs/stable/generated/torch.nn.Conv1d.html) and raw signal\n- Channel shuffling as an augmentation technique", "1530798": "Thanks for this collection of shared solution. \nMerci! Have a nice day :)", "1531087": "I am glad it helps, let me know if you learn something new. :)", "1532718": "Amazing work. thank u for collect these good places.", "1532762": "Thanks and most importantly thanks to those that made these write-ups and solutions.", "1559905": "Hey All,\n\nThank you all for taking part in our competition. The participation has been overwhelmingly positive. We are currently conducting a survey to gauge the demographic and outreach achieved. Kindly spare 2min and fill in this survey https://forms.gle/QP9L16niPexozyhu5.\n\nThank you all,\n\nRegards,\nChris" }, "source": "meta" }