Best practices in machine learning for chemistry.
Saved in:
| Title: | Best practices in machine learning for chemistry. |
|---|---|
| Authors: | Artrith N; Department of Chemical Engineering, Columbia University, New York, NY, USA. na2782@columbia.edu.; Columbia Center for Computational Electrochemistry (CCCE), Columbia University, New York, NY, USA. na2782@columbia.edu., Butler KT; SciML, Scientific Computing Department, STFC Rutherford Appleton Laboratory, Harwell Campus, Didcot, UK. keith.butler@stfc.ac.uk., Coudert FX; Chimie ParisTech, PSL University, CNRS, Institut de Recherche de Chimie Paris, Paris, France. fx.coudert@chimieparistech.psl.eu., Han S; Department of Materials Science and Engineering, Seoul National University, Seoul, Korea. hansw@snu.ac.kr., Isayev O; Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania, PA, USA. olexandr@olexandrisayev.com.; Department of Chemistry, Mellon College of Science, Carnegie Mellon University, Pittsburgh, PA, USA. olexandr@olexandrisayev.com., Jain A; Energy Technologies Area, Lawrence Berkeley National Laboratory, Berkeley, California, USA. ajain@lbl.gov., Walsh A; Department of Materials, Imperial College London, London, UK. a.walsh@imperial.ac.uk.; Department of Materials Science and Engineering, Yonsei University, Seoul, Korea. a.walsh@imperial.ac.uk. |
| Source: | Nature chemistry [Nat Chem] 2021 Jun; Vol. 13 (6), pp. 505-508. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Nature Pub. Group Country of Publication: England NLM ID: 101499734 Publication Model: Print Cited Medium: Internet ISSN: 1755-4349 (Electronic) Linking ISSN: 17554330 NLM ISO Abbreviation: Nat Chem Subsets: MEDLINE; PubMed not MEDLINE |
| Database: | MEDLINE Ultimate |
| FullText | Text: Availability: 0 |
|---|---|
| Header | DbId: mdl DbLabel: MEDLINE Ultimate An: 34059804 AccessLevel: 2 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
| IllustrationInfo | |
| Items | – Name: Title Label: Title Group: Ti Data: Best practices in machine learning for chemistry. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AU" term="%22Artrith+N%22">Artrith N</searchLink>; Department of Chemical Engineering, Columbia University, New York, NY, USA. na2782@columbia.edu.; Columbia Center for Computational Electrochemistry (CCCE), Columbia University, New York, NY, USA. na2782@columbia.edu.<br /><searchLink fieldCode="AU" term="%22Butler+KT%22">Butler KT</searchLink>; SciML, Scientific Computing Department, STFC Rutherford Appleton Laboratory, Harwell Campus, Didcot, UK. keith.butler@stfc.ac.uk.<br /><searchLink fieldCode="AU" term="%22Coudert+FX%22">Coudert FX</searchLink>; Chimie ParisTech, PSL University, CNRS, Institut de Recherche de Chimie Paris, Paris, France. fx.coudert@chimieparistech.psl.eu.<br /><searchLink fieldCode="AU" term="%22Han+S%22">Han S</searchLink>; Department of Materials Science and Engineering, Seoul National University, Seoul, Korea. hansw@snu.ac.kr.<br /><searchLink fieldCode="AU" term="%22Isayev+O%22">Isayev O</searchLink>; Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania, PA, USA. olexandr@olexandrisayev.com.; Department of Chemistry, Mellon College of Science, Carnegie Mellon University, Pittsburgh, PA, USA. olexandr@olexandrisayev.com.<br /><searchLink fieldCode="AU" term="%22Jain+A%22">Jain A</searchLink>; Energy Technologies Area, Lawrence Berkeley National Laboratory, Berkeley, California, USA. ajain@lbl.gov.<br /><searchLink fieldCode="AU" term="%22Walsh+A%22">Walsh A</searchLink>; Department of Materials, Imperial College London, London, UK. a.walsh@imperial.ac.uk.; Department of Materials Science and Engineering, Yonsei University, Seoul, Korea. a.walsh@imperial.ac.uk. – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22101499734%22">Nature chemistry</searchLink> [Nat Chem] 2021 Jun; Vol. 13 (6), pp. 505-508. – Name: TypePub Label: Publication Type Group: TypPub Data: Journal Article – Name: TitleSource Label: Journal Info Group: Src Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22Nature+Pub%2E+Group%22">Nature Pub. Group </searchLink><i>Country of Publication: </i>England <i>NLM ID: </i>101499734 <i>Publication Model: </i>Print <i>Cited Medium: </i>Internet <i>ISSN: </i>1755-4349 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2217554330%22">17554330 </searchLink><i>NLM ISO Abbreviation: </i>Nat Chem <i>Subsets: </i>MEDLINE; PubMed not MEDLINE |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=mdl&AN=34059804 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1038/s41557-021-00716-z Languages: – Code: eng Text: English PhysicalDescription: Pagination: StartPage: 505 Titles: – TitleFull: Best practices in machine learning for chemistry. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Artrith N – PersonEntity: Name: NameFull: Butler KT – PersonEntity: Name: NameFull: Coudert FX – PersonEntity: Name: NameFull: Han S – PersonEntity: Name: NameFull: Isayev O – PersonEntity: Name: NameFull: Jain A – PersonEntity: Name: NameFull: Walsh A IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 06 Text: 2021 Jun Type: published Y: 2021 Identifiers: – Type: issn-electronic Value: 1755-4349 Numbering: – Type: volume Value: 13 – Type: issue Value: 6 Titles: – TitleFull: Nature chemistry Type: main |
| ResultId | 1 |
