What Does the Machine Learn? Knowledge Representations of Chemical Reactivity
Author:
Affiliation:
1. Department of Chemistry, University of Michigan, 930 North University Avenue, Ann Arbor, Michigan 48109, United States
2. Department of Statistics, University of Michigan, 1085 South University Avenue, Ann Arbor, Michigan 48109, United States
Funder
Division of Chemistry
National Institute of General Medical Sciences
Publisher
American Chemical Society (ACS)
Subject
Library and Information Sciences,Computer Science Applications,General Chemical Engineering,General Chemistry
Link
https://pubs.acs.org/doi/pdf/10.1021/acs.jcim.9b00721
Reference79 articles.
1. Assessment and Validation of Machine Learning Methods for Predicting Molecular Atomization Energies
2. Machine Learning Methods to Predict Density Functional Theory B3LYP Energies of HOMO and LUMO Orbitals
3. Machine-learning-assisted materials discovery using failed experiments
4. A Quantitative Model for the Prediction of Sooting Tendency from Molecular Structure
5. Automatic Chemical Design Using a Data-Driven Continuous Representation of Molecules
Cited by 19 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Machine Learning Strategies for Reaction Development: Toward the Low-Data Limit;Journal of Chemical Information and Modeling;2023-06-14
2. Improving Accuracy and Transferability of Machine Learning Chemical Activation Energies by Adding Electronic Structure Information;Journal of Chemical Information and Modeling;2023-03-03
3. Benchmark of general-purpose machine learning-based quantum mechanical method AIQM1 on reaction barrier heights;The Journal of Chemical Physics;2023-02-15
4. Explainable Solvation Free Energy Prediction Combining Graph Neural Networks with Chemical Intuition;Journal of Chemical Information and Modeling;2022-11-01
5. Successes and challenges in using machine-learned activation energies in kinetic simulations;The Journal of Chemical Physics;2022-07-07
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3