Hey Kagglers,
\nWe’re happy to announce the conclusion of the Bristol-Myers Squibb - Molecular Translation competition! We’d been working with the BMS team for a long time now in forming a competition, and we were excited to see it come together!
\nThis year’s competition ended with 1,171 participants on 874 teams! We had 10,237 submissions from 64 countries! For 146 users (including all 3 of our 1st place winners, and 24 users on top 100 teams!), this was their first competition. We also had 5 new Grandmasters and 9 new Masters at the conclusion of the competition! Thank you all for your hard work in this competition and congratulations to our winners and to those who gained a new ranking!
\nAs said before, we were once again very pleased to work with the team at BMS (Yvette and Jake). A special shout out to Geoff Stamper who kicked off the initial conversations while he was at BMS in the fall of 2019. We're glad they chose Kaggle to be a platform to bring these types of problems to the broader data science community. They've been a pleasure to work with, and we hope to work with them again in the future.
\nWe're also continually pleased to see how Kaggle Competitions serve as a great medium and vehicle through which the greater data science community can learn and develop their machine learning abilities and skills. Beginners and experts can come together to start, grow, and succeed. Further, in this competition, many can use their machine learning skills to help a great cause like this one.
\nWe've cleaned the leaderboard and disqualified some teams that have violated the rules. If you think you were removed by mistake, or believe you have evidence that suggests another team cheated, please contact compliance. Please fill in all the fields honestly.
\nThe top potential winning teams have been contacted via email to provide their winning solutions for host review. Should we need to move down the leaderboard for any reason, we will do so and continue to make contact with subsequent teams.
\nYou should have already seen your points and medals awarded, however it may take a few hours to propagate through if yours are still missing.
\nIn the meantime, I've created this thread to be a curated list of your work. As you post your solutions, top kernels, and general discussion posts, I'll update this thread to keep track. If you write a paper, thesis, or present at a conference, and would like to share your work, please let us know so we can share with the Kaggle community! Additionally, if you performed any data manipulation, or used a new technique in this competition that you'd like to share to further the industry, please let us know and we'll post it here! That way, should you be looking for takeaways in the future, or if you've just now stumbled across the competition, you have a place to see what surfaced from the work performed.
\nHappy Modeling!
\nKaggle Team
Hey Kagglers,
\nWe’re happy to announce the conclusion of the Bristol-Myers Squibb - Molecular Translation competition! We’d been working with the BMS team for a long time now in forming a competition, and we were excited to see it come together!
\nThis year’s competition ended with 1,171 participants on 874 teams! We had 10,237 submissions from 64 countries! For 146 users (including all 3 of our 1st place winners, and 24 users on top 100 teams!), this was their first competition. We also had 5 new Grandmasters and 9 new Masters at the conclusion of the competition! Thank you all for your hard work in this competition and congratulations to our winners and to those who gained a new ranking!
\nAs said before, we were once again very pleased to work with the team at BMS (Yvette and Jake). A special shout out to Geoff Stamper who kicked off the initial conversations while he was at BMS in the fall of 2019. We're glad they chose Kaggle to be a platform to bring these types of problems to the broader data science community. They've been a pleasure to work with, and we hope to work with them again in the future.
\nWe're also continually pleased to see how Kaggle Competitions serve as a great medium and vehicle through which the greater data science community can learn and develop their machine learning abilities and skills. Beginners and experts can come together to start, grow, and succeed. Further, in this competition, many can use their machine learning skills to help a great cause like this one.
\nWe've cleaned the leaderboard and disqualified some teams that have violated the rules. If you think you were removed by mistake, or believe you have evidence that suggests another team cheated, please contact compliance. Please fill in all the fields honestly.
\nThe top potential winning teams have been contacted via email to provide their winning solutions for host review. Should we need to move down the leaderboard for any reason, we will do so and continue to make contact with subsequent teams.
\nYou should have already seen your points and medals awarded, however it may take a few hours to propagate through if yours are still missing.
\nIn the meantime, I've created this thread to be a curated list of your work. As you post your solutions, top kernels, and general discussion posts, I'll update this thread to keep track. If you write a paper, thesis, or present at a conference, and would like to share your work, please let us know so we can share with the Kaggle community! Additionally, if you performed any data manipulation, or used a new technique in this competition that you'd like to share to further the industry, please let us know and we'll post it here! That way, should you be looking for takeaways in the future, or if you've just now stumbled across the competition, you have a place to see what surfaced from the work performed.
\nHappy Modeling!
\nKaggle Team
There is a typoz in the 2nd paragraph
\nThis year’s competition ended with 1,171 participants on 274 teams!
but there are 874 teams not 274
", "rawMarkdown": "There is a typoz in the 2nd paragraph\n`This year’s competition ended with 1,171 participants on 274 teams!`\n\nbut there are 874 teams not 274", "votes": null }, { "id": "1344339", "postDate": "06/10/2021 20:28:04", "content": "Corrected! Good find.
", "rawMarkdown": "Corrected! Good find.", "votes": null }, { "id": "1395208", "postDate": "07/21/2021 03:16:18", "content": "Where is the first and second winner solution?
", "rawMarkdown": "Where is the first and second winner solution?", "votes": null }, { "id": "1585656", "postDate": "11/17/2021 12:14:03", "content": "Good question; I would be much interested in their solutions.
", "rawMarkdown": "Good question; I would be much interested in their solutions.", "votes": null } ], "comments": [ { "id": 1344332, "author_name": "morizin", "author_url": "", "post_date": "06/10/2021 20:18:32", "content": "There is a typoz in the 2nd paragraph
\nThis year’s competition ended with 1,171 participants on 274 teams!
but there are 874 teams not 274
", "votes": null, "replies": [ { "id": 1344339, "author_name": "addisonhoward", "author_url": "", "post_date": "06/10/2021 20:28:04", "content": "Corrected! Good find.
", "votes": null, "replies": [] } ] }, { "id": 1395208, "author_name": "drankdock", "author_url": "", "post_date": "07/21/2021 03:16:18", "content": "Where is the first and second winner solution?
", "votes": null, "replies": [ { "id": 1585656, "author_name": "nofreewill", "author_url": "", "post_date": "11/17/2021 12:14:03", "content": "Good question; I would be much interested in their solutions.
", "votes": null, "replies": [] } ] } ], "raw_markdown_by_id": { "1344293": "Hey Kagglers,\n\nWe’re happy to announce the conclusion of the Bristol-Myers Squibb - Molecular Translation competition! We’d been working with the BMS team for a long time now in forming a competition, and we were excited to see it come together!\n\nThis year’s competition ended with 1,171 participants on 874 teams! We had 10,237 submissions from 64 countries! For 146 users (including all 3 of our 1st place winners, and 24 users on top 100 teams!), this was their first competition. We also had 5 new Grandmasters and 9 new Masters at the conclusion of the competition! Thank you all for your hard work in this competition and congratulations to our winners and to those who gained a new ranking! \n\nAs said before, we were once again very pleased to work with the team at BMS ([Yvette](https://www.kaggle.com/yvettelincoln) and [Jake](https://www.kaggle.com/jakealbrecht1337l)). A special shout out to Geoff Stamper who kicked off the initial conversations while he was at BMS in the fall of 2019. We're glad they chose Kaggle to be a platform to bring these types of problems to the broader data science community. They've been a pleasure to work with, and we hope to work with them again in the future. \n\nWe're also continually pleased to see how Kaggle Competitions serve as a great medium and vehicle through which the greater data science community can learn and develop their machine learning abilities and skills. Beginners and experts can come together to start, grow, and succeed. Further, in this competition, many can use their machine learning skills to help a great cause like this one.\n\nWe've cleaned the leaderboard and disqualified some teams that have violated the rules. If you think you were removed by mistake, or believe you have evidence that suggests another team cheated, please contact [compliance](https://www.kaggle.com/compliance). Please fill in all the fields honestly.\n\nThe top potential winning teams have been contacted via email to provide their winning solutions for host review. Should we need to move down the leaderboard for any reason, we will do so and continue to make contact with subsequent teams.\n\nYou should have already seen your points and medals awarded, however it may take a few hours to propagate through if yours are still missing.\n\nIn the meantime, I've created this thread to be a curated list of your work. As you post your solutions, top kernels, and general discussion posts, I'll update this thread to keep track. If you write a paper, thesis, or present at a conference, and would like to share your work, please let us know so we can share with the Kaggle community! Additionally, if you performed any data manipulation, or used a new technique in this competition that you'd like to share to further the industry, please let us know and we'll post it here! That way, should you be looking for takeaways in the future, or if you've just now stumbled across the competition, you have a place to see what surfaced from the work performed.\n\nHappy Modeling!\nKaggle Team\n\n###Top Solution Write-ups\n\n- [3rd Place](https://www.kaggle.com/c/bms-molecular-translation/discussion/243932)\n- [4th Place](https://www.kaggle.com/c/bms-molecular-translation/discussion/243787)\n- [5th Place](https://www.kaggle.com/c/bms-molecular-translation/discussion/243943)\n- [6th Place](https://www.kaggle.com/c/bms-molecular-translation/discussion/245704)\n- [7th Place](https://www.kaggle.com/c/bms-molecular-translation/discussion/243779)\n- [8th Place](https://www.kaggle.com/c/bms-molecular-translation/discussion/244078)\n- [9th Place a](https://www.kaggle.com/c/bms-molecular-translation/discussion/244031)\n- [9th Place b](https://www.kaggle.com/c/bms-molecular-translation/discussion/243761)\n- [10th Place a](https://www.kaggle.com/c/bms-molecular-translation/discussion/243766)\n- [10th Place b](https://www.kaggle.com/c/bms-molecular-translation/discussion/243809)\n- [12th Place](https://www.kaggle.com/c/bms-molecular-translation/discussion/243824)\n- [13th Place](https://www.kaggle.com/c/bms-molecular-translation/discussion/244166)\n- [15th Place](https://www.kaggle.com/c/bms-molecular-translation/discussion/243951)\n- [18th Place](https://www.kaggle.com/c/bms-molecular-translation/discussion/244266)\n- [24th Place](https://www.kaggle.com/c/bms-molecular-translation/discussion/243917)\n- [47th Place](https://www.kaggle.com/c/bms-molecular-translation/discussion/243845)\n- [50th Place](https://www.kaggle.com/c/bms-molecular-translation/discussion/243820)\n\n\n###Top Notebooks\n- [InChI / Resnet + LSTM with attention / starter](https://www.kaggle.com/yasufuminakama/inchi-resnet-lstm-with-attention-starter)\n- [Molecular Translation - Exploratory Data Analysis](https://www.kaggle.com/ihelon/molecular-translation-exploratory-data-analysis)\n- [InChI / preprocess / 2](https://www.kaggle.com/yasufuminakama/inchi-preprocess-2)\n- [Improved synthetic data for BMS competition (v3)](https://www.kaggle.com/stainsby/improved-synthetic-data-for-bms-competition-v3)\n- [Tensorflow TPU Training Baseline LB 16.92🔥](https://www.kaggle.com/markwijkhuizen/tensorflow-tpu-training-baseline-lb-16-92)\n- [Letter Retrieval \\ Molecular Translation](https://www.kaggle.com/thomaskonstantin/letter-retrieval-molecular-translation)\n\n###Other Top Discussions\n- [[completed] transformer starter kit ... in pytorch](https://www.kaggle.com/c/bms-molecular-translation/discussion/231190)\n- [Resnet + LSTM with attention starter](https://www.kaggle.com/c/bms-molecular-translation/discussion/225856)\n- [🎊 🎉 Research Papers in Deep Learning and Chemical Structures🌟 ✨ (Image Data)](https://www.kaggle.com/c/bms-molecular-translation/discussion/223218)\n- [Best Single Model](https://www.kaggle.com/c/bms-molecular-translation/discussion/224257)\n- [Winning solutions from similar competition: Molecular Translation into SMILES](https://www.kaggle.com/c/bms-molecular-translation/discussion/223381)", "1344332": "There is a typoz in the 2nd paragraph\n`This year’s competition ended with 1,171 participants on 274 teams!`\n\nbut there are 874 teams not 274", "1344339": "Corrected! Good find.", "1395208": "Where is the first and second winner solution?", "1585656": "Good question; I would be much interested in their solutions." }, "source": "meta" }