Please use this thread to list the pre-trained models you are planning to use, or other external data. Once a model or data source has been posted once, it does not need to be posted again. You must post here one week prior to competition close.
", "messages": [ { "id": "453857", "postDate": "01/10/2019 22:41:42", "content": "Please use this thread to list the pre-trained models you are planning to use, or other external data. Once a model or data source has been posted once, it does not need to be posted again. You must post here one week prior to competition close.
", "rawMarkdown": "Please use this thread to list the pre-trained models you are planning to use, or other external data. Once a model or data source has been posted once, it does not need to be posted again. You must post here one week prior to competition close.", "votes": null }, { "id": "464242", "postDate": "01/31/2019 13:01:40", "content": "As pre-trained models are allowed in this competition I reserve the right to use my models https://www.kaggle.com/scirpus/andrews-script-plus-a-genetic-program-model
\n\nJust to see how far we can push the rules - LOL
", "rawMarkdown": "As pre-trained models are allowed in this competition I reserve the right to use my models https://www.kaggle.com/scirpus/andrews-script-plus-a-genetic-program-model\n\nJust to see how far we can push the rules - LOL", "votes": null }, { "id": "515067", "postDate": "04/12/2019 06:47:05", "content": "@inversion, can you elaborate on what should be posted here for people who are relatively new to Kaggle?
", "rawMarkdown": "inversion, can you elaborate on what should be posted here for people who are relatively new to Kaggle?", "votes": null }, { "id": "516555", "postDate": "04/14/2019 12:04:22", "content": "External data listed here: https://sites.psu.edu/chasbolton/
", "rawMarkdown": "External data listed here: https://sites.psu.edu/chasbolton/", "votes": null }, { "id": "520120", "postDate": "04/20/2019 07:56:55", "content": "lol
", "rawMarkdown": "lol", "votes": null }, { "id": "523604", "postDate": "04/26/2019 15:47:04", "content": "Are we allowed to use the data derived from the earlier publication: https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2018GL079712 ?
", "rawMarkdown": "Are we allowed to use the data derived from the earlier publication: https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2018GL079712 ?", "votes": null }, { "id": "525052", "postDate": "04/30/2019 05:25:32", "content": "I've been trying to learn fastai on this dataset- so I may end up using the pretrained imagenet models in my solution. Also I happened to stumble upon some public github repos that had helpful code/ideas.
", "rawMarkdown": "I've been trying to learn fastai on this dataset- so I may end up using the pretrained imagenet models in my solution. Also I happened to stumble upon some public github repos that had helpful code/ideas.", "votes": null }, { "id": "527267", "postDate": "05/05/2019 01:16:49", "content": "Keras Pretrained Models:\nhttps://github.com/keras-team/keras-applications
\n\nPyTorch Pretrained Models:\nhttps://github.com/Cadene/pretrained-models.pytorch
", "rawMarkdown": "Keras Pretrained Models:\nhttps://github.com/keras-team/keras-applications\n\nPyTorch Pretrained Models:\nhttps://github.com/Cadene/pretrained-models.pytorch", "votes": null }, { "id": "537116", "postDate": "05/26/2019 08:09:03", "content": "Just to be safe, I am disclosing publicly that I am using experiments found in the link shared above.
", "rawMarkdown": "Just to be safe, I am disclosing publicly that I am using experiments found in the link shared above.", "votes": null }, { "id": "537401", "postDate": "05/27/2019 00:17:19", "content": "Just to make sure: preprocessed p4581 data by @leighplt, @redstr \n - https://www.kaggle.com/leighplt/laboratory-acoustic-data-exp4581\n - https://www.kaggle.com/redstr/lanl-p4581
", "rawMarkdown": "Just to make sure: preprocessed p4581 data by @leighplt, @redstr \n - https://www.kaggle.com/leighplt/laboratory-acoustic-data-exp4581\n - https://www.kaggle.com/redstr/lanl-p4581", "votes": null }, { "id": "537408", "postDate": "05/27/2019 00:47:55", "content": "@corochann can you comment on which set is superior?
", "rawMarkdown": "corochann can you comment on which set is superior?", "votes": null }, { "id": "537429", "postDate": "05/27/2019 02:36:15", "content": "preprocessed p4581 data by @leighplt, @redstr
\n\nhttps://www.kaggle.com/leighplt/laboratory-acoustic-data-exp4581\nhttps://www.kaggle.com/redstr/lanl-p4581
", "rawMarkdown": "preprocessed p4581 data by @leighplt, @redstr\n\nhttps://www.kaggle.com/leighplt/laboratory-acoustic-data-exp4581\nhttps://www.kaggle.com/redstr/lanl-p4581", "votes": null }, { "id": "537671", "postDate": "05/27/2019 12:46:12", "content": "Please refer https://www.kaggle.com/c/LANL-Earthquake-Prediction/discussion/90838\nIt seems https://www.kaggle.com/leighplt/laboratory-acoustic-data-exp4581 contains processed ttf info as well.
", "rawMarkdown": "Please refer https://www.kaggle.com/c/LANL-Earthquake-Prediction/discussion/90838\nIt seems https://www.kaggle.com/leighplt/laboratory-acoustic-data-exp4581 contains processed ttf info as well.", "votes": null }, { "id": "542832", "postDate": "06/04/2019 06:09:33", "content": "Did anyone actually used these datasets? They were so large so I just gave up.\n@corochann you seem to have a pretty cozy place on the Leaderboard, did the datasets help?\nAlso, I wonder why is no one using p2394, the original LANL paper made their observations on this dataset.
", "rawMarkdown": "Did anyone actually used these datasets? They were so large so I just gave up.\n@corochann you seem to have a pretty cozy place on the Leaderboard, did the datasets help?\nAlso, I wonder why is no one using p2394, [the original LANL paper ](https://arxiv.org/ftp/arxiv/papers/1702/1702.05774.pdf)made their observations on this dataset.", "votes": null }, { "id": "543547", "postDate": "06/04/2019 15:30:35", "content": "@spacebunny \nI wrote summary of our approach, please check!\nhttps://www.kaggle.com/c/LANL-Earthquake-Prediction/discussion/94450
\n\nI used the data, but actually its performance change is not so significant.\nI think our place comes from different point, not from this data.
\n\nFor p2394, its data sampling frequency is different (kHz order while our dataset is MHz order). I concluded it's difficult to use p2394 data.
", "rawMarkdown": "spacebunny \nI wrote summary of our approach, please check!\nhttps://www.kaggle.com/c/LANL-Earthquake-Prediction/discussion/94450\n\nI used the data, but actually its performance change is not so significant.\nI think our place comes from different point, not from this data.\n\nFor p2394, its data sampling frequency is different (kHz order while our dataset is MHz order). I concluded it's difficult to use p2394 data.", "votes": null } ], "comments": [ { "id": 464242, "author_name": "scirpus", "author_url": "", "post_date": "01/31/2019 13:01:40", "content": "As pre-trained models are allowed in this competition I reserve the right to use my models https://www.kaggle.com/scirpus/andrews-script-plus-a-genetic-program-model
\n\nJust to see how far we can push the rules - LOL
", "votes": null, "replies": [ { "id": 520120, "author_name": "mhviraf", "author_url": "", "post_date": "04/20/2019 07:56:55", "content": "lol
", "votes": null, "replies": [] } ] }, { "id": 515067, "author_name": "pzegadlo", "author_url": "", "post_date": "04/12/2019 06:47:05", "content": "@inversion, can you elaborate on what should be posted here for people who are relatively new to Kaggle?
", "votes": null, "replies": [] }, { "id": 516555, "author_name": "anjum48", "author_url": "", "post_date": "04/14/2019 12:04:22", "content": "External data listed here: https://sites.psu.edu/chasbolton/
", "votes": null, "replies": [ { "id": 537116, "author_name": "teeyee314", "author_url": "", "post_date": "05/26/2019 08:09:03", "content": "Just to be safe, I am disclosing publicly that I am using experiments found in the link shared above.
", "votes": null, "replies": [] }, { "id": 537401, "author_name": "corochann", "author_url": "", "post_date": "05/27/2019 00:17:19", "content": "Just to make sure: preprocessed p4581 data by @leighplt, @redstr \n - https://www.kaggle.com/leighplt/laboratory-acoustic-data-exp4581\n - https://www.kaggle.com/redstr/lanl-p4581
", "votes": null, "replies": [] }, { "id": 537408, "author_name": "teeyee314", "author_url": "", "post_date": "05/27/2019 00:47:55", "content": "@corochann can you comment on which set is superior?
", "votes": null, "replies": [] }, { "id": 537671, "author_name": "corochann", "author_url": "", "post_date": "05/27/2019 12:46:12", "content": "Please refer https://www.kaggle.com/c/LANL-Earthquake-Prediction/discussion/90838\nIt seems https://www.kaggle.com/leighplt/laboratory-acoustic-data-exp4581 contains processed ttf info as well.
", "votes": null, "replies": [] }, { "id": 542832, "author_name": "spacebunny", "author_url": "", "post_date": "06/04/2019 06:09:33", "content": "Did anyone actually used these datasets? They were so large so I just gave up.\n@corochann you seem to have a pretty cozy place on the Leaderboard, did the datasets help?\nAlso, I wonder why is no one using p2394, the original LANL paper made their observations on this dataset.
", "votes": null, "replies": [] }, { "id": 543547, "author_name": "corochann", "author_url": "", "post_date": "06/04/2019 15:30:35", "content": "@spacebunny \nI wrote summary of our approach, please check!\nhttps://www.kaggle.com/c/LANL-Earthquake-Prediction/discussion/94450
\n\nI used the data, but actually its performance change is not so significant.\nI think our place comes from different point, not from this data.
\n\nFor p2394, its data sampling frequency is different (kHz order while our dataset is MHz order). I concluded it's difficult to use p2394 data.
", "votes": null, "replies": [] } ] }, { "id": 523604, "author_name": "redstr", "author_url": "", "post_date": "04/26/2019 15:47:04", "content": "Are we allowed to use the data derived from the earlier publication: https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2018GL079712 ?
", "votes": null, "replies": [] }, { "id": 525052, "author_name": "robikscube", "author_url": "", "post_date": "04/30/2019 05:25:32", "content": "I've been trying to learn fastai on this dataset- so I may end up using the pretrained imagenet models in my solution. Also I happened to stumble upon some public github repos that had helpful code/ideas.
", "votes": null, "replies": [] }, { "id": 527267, "author_name": "markpeng", "author_url": "", "post_date": "05/05/2019 01:16:49", "content": "Keras Pretrained Models:\nhttps://github.com/keras-team/keras-applications
\n\nPyTorch Pretrained Models:\nhttps://github.com/Cadene/pretrained-models.pytorch
", "votes": null, "replies": [] }, { "id": 537429, "author_name": "khyeh0719", "author_url": "", "post_date": "05/27/2019 02:36:15", "content": "preprocessed p4581 data by @leighplt, @redstr
\n\nhttps://www.kaggle.com/leighplt/laboratory-acoustic-data-exp4581\nhttps://www.kaggle.com/redstr/lanl-p4581
", "votes": null, "replies": [] } ], "raw_markdown_by_id": { "453857": "Please use this thread to list the pre-trained models you are planning to use, or other external data. Once a model or data source has been posted once, it does not need to be posted again. You must post here one week prior to competition close.", "464242": "As pre-trained models are allowed in this competition I reserve the right to use my models https://www.kaggle.com/scirpus/andrews-script-plus-a-genetic-program-model\n\nJust to see how far we can push the rules - LOL", "515067": "inversion, can you elaborate on what should be posted here for people who are relatively new to Kaggle?", "516555": "External data listed here: https://sites.psu.edu/chasbolton/", "520120": "lol", "523604": "Are we allowed to use the data derived from the earlier publication: https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2018GL079712 ?", "525052": "I've been trying to learn fastai on this dataset- so I may end up using the pretrained imagenet models in my solution. Also I happened to stumble upon some public github repos that had helpful code/ideas.", "527267": "Keras Pretrained Models:\nhttps://github.com/keras-team/keras-applications\n\nPyTorch Pretrained Models:\nhttps://github.com/Cadene/pretrained-models.pytorch", "537116": "Just to be safe, I am disclosing publicly that I am using experiments found in the link shared above.", "537401": "Just to make sure: preprocessed p4581 data by @leighplt, @redstr \n - https://www.kaggle.com/leighplt/laboratory-acoustic-data-exp4581\n - https://www.kaggle.com/redstr/lanl-p4581", "537408": "corochann can you comment on which set is superior?", "537429": "preprocessed p4581 data by @leighplt, @redstr\n\nhttps://www.kaggle.com/leighplt/laboratory-acoustic-data-exp4581\nhttps://www.kaggle.com/redstr/lanl-p4581", "537671": "Please refer https://www.kaggle.com/c/LANL-Earthquake-Prediction/discussion/90838\nIt seems https://www.kaggle.com/leighplt/laboratory-acoustic-data-exp4581 contains processed ttf info as well.", "542832": "Did anyone actually used these datasets? They were so large so I just gave up.\n@corochann you seem to have a pretty cozy place on the Leaderboard, did the datasets help?\nAlso, I wonder why is no one using p2394, [the original LANL paper ](https://arxiv.org/ftp/arxiv/papers/1702/1702.05774.pdf)made their observations on this dataset.", "543547": "spacebunny \nI wrote summary of our approach, please check!\nhttps://www.kaggle.com/c/LANL-Earthquake-Prediction/discussion/94450\n\nI used the data, but actually its performance change is not so significant.\nI think our place comes from different point, not from this data.\n\nFor p2394, its data sampling frequency is different (kHz order while our dataset is MHz order). I concluded it's difficult to use p2394 data." }, "source": "meta" }