Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Will Gerrard"'
Autor:
Lars A Bratholm, Will Gerrard, Brandon Anderson, Shaojie Bai, Sunghwan Choi, Lam Dang, Pavel Hanchar, Addison Howard, Sanghoon Kim, Zico Kolter, Risi Kondor, Mordechai Kornbluth, Youhan Lee, Youngsoo Lee, Jonathan P Mailoa, Thanh Tu Nguyen, Milos Popovic, Goran Rakocevic, Walter Reade, Wonho Song, Luka Stojanovic, Erik H Thiede, Nebojsa Tijanic, Andres Torrubia, Devin Willmott, Craig P Butts, David R Glowacki
Publikováno v:
PLoS ONE, Vol 16, Iss 7, p e0253612 (2021)
The rise of machine learning (ML) has created an explosion in the potential strategies for using data to make scientific predictions. For physical scientists wishing to apply ML strategies to a particular domain, it can be difficult to assess in adva
Externí odkaz:
https://doaj.org/article/7bd641a416ff403b90f3c0a0e9726773
Publikováno v:
Gerrard, W, Yiu, C & Butts, C P 2021, ' Prediction of 15N chemical shifts by machine learning ', Magnetic Resonance in Chemistry, vol. (2021), no. SPECIAL ISSUE RESEARCH ARTICLE . https://doi.org/10.1002/mrc.5208
We demonstrate the potential for machine learning systems to predict three-dimensional (3D)-relevant NMR properties beyond traditional 1 H- and 13 C-based data, with comparable accuracy to density functional theory (DFT) (but orders of magnitude fast
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::607d31d57c1fd1bcf013028785f83ab1
https://doi.org/10.1002/mrc.5208
https://doi.org/10.1002/mrc.5208
Publikováno v:
Magnetic resonance in chemistry : MRCREFERENCES. 60(11)
We demonstrate the potential for machine learning systems to predict three-dimensional (3D)-relevant NMR properties beyond traditional
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid________::5076fc4a2cfe18b3b159440dd6b026c6
https://pubmed.ncbi.nlm.nih.gov/34407565
https://pubmed.ncbi.nlm.nih.gov/34407565
A community-powered search of machine learning strategy space to find NMR property prediction models
Autor:
Zico Kolter, Mordechai Kornbluth, Sanghoon Kim, Lars Andersen Bratholm, Risi Kondor, Jonathan P. Mailoa, Youngsoo Lee, Lam Dang, Goran Rakocevic, Brandon Anderson, Shaojie Bai, Will Gerrard, Milos R. Popovic, David R. Glowacki, Sunghwan Choi, Craig P. Butts, Thanh Tu Nguyen, Devin Willmott, Erik H. Thiede, Luka Stojanovic, Youhan Lee, Nebojsa Tijanic, Addison Howard, Wonho Song, Walter Reade, Andres Torrubia, Pavel Hanchar
Publikováno v:
PLoS ONE, Vol 16, Iss 7, p e0253612 (2021)
Bratholm, L A, Gerrard, W, Anderson, B, Bai, S, Choi, S, Dang, L, Hanchar, P, Howard, A, Kim, S, Kolter, Z, Kondor, R, Kornbluth, M, Lee, Y, Lee, Y, Mailoa, J P, Nguyen, T T, Popovic, M, Rakocevic, G, Reade, W, Song, W, Stojanovic, L, Thiede, E H, Tijanic, N, Torrubia, A, Willmott, D, Butts, C P & Glowacki, D R 2021, ' A community-powered search of machine learning strategy space to find NMR property prediction models ', PLoS ONE, vol. 16, no. 7, e0253612 . https://doi.org/10.1371/journal.pone.0253612
PLoS ONE
Bratholm, L A, Gerrard, W, Anderson, B, Bai, S, Choi, S, Dang, L, Hanchar, P, Howard, A, Kim, S, Kolter, Z, Kondor, R, Kornbluth, M, Lee, Y, Lee, Y, Mailoa, J P, Nguyen, T T, Popovic, M, Rakocevic, G, Reade, W, Song, W, Stojanovic, L, Thiede, E H, Tijanic, N, Torrubia, A, Willmott, D, Butts, C P & Glowacki, D R 2021, ' A community-powered search of machine learning strategy space to find NMR property prediction models ', PLoS ONE, vol. 16, no. 7, e0253612 . https://doi.org/10.1371/journal.pone.0253612
PLoS ONE
The rise of machine learning (ML) has created an explosion in the potential strategies for using data to make scientific predictions. For physical scientists wishing to apply ML strategies to a particular domain, it can be difficult to assess in adva
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::672ab3f6c2ed91044cbf5995b3323ede
http://arxiv.org/abs/2008.05994
http://arxiv.org/abs/2008.05994
Autor:
Martin J. Packer, Adrian J. Mulholland, David R. Glowacki, Will Gerrard, Lars Andersen Bratholm, Craig P. Butts
Publikováno v:
Chemical Science
Gerrard, W, Bratholm, L A, Packer, M J, Mulholland, A J, Glowacki, D R & Butts, C P 2020, ' IMPRESSION – prediction of NMR parameters for 3-dimensional chemical structures using machine learning with near quantum chemical accuracy ', Chemical Science, vol. 11, no. 2, pp. 508-515 . https://doi.org/10.1039/C9SC03854J
Gerrard, W, Bratholm, L A, Packer, M J, Mulholland, A J, Glowacki, D R & Butts, C P 2020, ' IMPRESSION – prediction of NMR parameters for 3-dimensional chemical structures using machine learning with near quantum chemical accuracy ', Chemical Science, vol. 11, no. 2, pp. 508-515 . https://doi.org/10.1039/C9SC03854J
The IMPRESSION machine learning system can predict NMR parameters for 3D structures with similar results to DFT but in seconds rather than hours.
The IMPRESSION (Intelligent Machine PREdiction of Shift and Scalar information Of Nuclei) machine l
The IMPRESSION (Intelligent Machine PREdiction of Shift and Scalar information Of Nuclei) machine l
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c30ec442c9d68571b044baef4cb31708
https://pubmed.ncbi.nlm.nih.gov/32190270
https://pubmed.ncbi.nlm.nih.gov/32190270