{"title":"Small Data Machine Learning Approaches in Molecular and Materials Science","authors":"Siddarth K. Achar, John A. Keith","doi":"10.1021/acs.chemrev.4c00957","DOIUrl":null,"url":null,"abstract":"This article has not yet been cited by other publications.","PeriodicalId":32,"journal":{"name":"Chemical Reviews","volume":"73 1","pages":""},"PeriodicalIF":51.4000,"publicationDate":"2024-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Chemical Reviews","FirstCategoryId":"92","ListUrlMain":"https://doi.org/10.1021/acs.chemrev.4c00957","RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, MULTIDISCIPLINARY","Score":null,"Total":0}
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Abstract
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期刊介绍：
Chemical Reviews is a highly regarded and highest-ranked journal covering the general topic of chemistry. Its mission is to provide comprehensive, authoritative, critical, and readable reviews of important recent research in organic, inorganic, physical, analytical, theoretical, and biological chemistry.
Since 1985, Chemical Reviews has also published periodic thematic issues that focus on a single theme or direction of emerging research.
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