Jaundice
发表于 2025-3-21 17:20:40
书目名称Machine Learning in Molecular Sciences影响因子(影响力)<br> http://impactfactor.cn/2024/if/?ISSN=BK0620699<br><br> <br><br>书目名称Machine Learning in Molecular Sciences影响因子(影响力)学科排名<br> http://impactfactor.cn/2024/ifr/?ISSN=BK0620699<br><br> <br><br>书目名称Machine Learning in Molecular Sciences网络公开度<br> http://impactfactor.cn/2024/at/?ISSN=BK0620699<br><br> <br><br>书目名称Machine Learning in Molecular Sciences网络公开度学科排名<br> http://impactfactor.cn/2024/atr/?ISSN=BK0620699<br><br> <br><br>书目名称Machine Learning in Molecular Sciences被引频次<br> http://impactfactor.cn/2024/tc/?ISSN=BK0620699<br><br> <br><br>书目名称Machine Learning in Molecular Sciences被引频次学科排名<br> http://impactfactor.cn/2024/tcr/?ISSN=BK0620699<br><br> <br><br>书目名称Machine Learning in Molecular Sciences年度引用<br> http://impactfactor.cn/2024/ii/?ISSN=BK0620699<br><br> <br><br>书目名称Machine Learning in Molecular Sciences年度引用学科排名<br> http://impactfactor.cn/2024/iir/?ISSN=BK0620699<br><br> <br><br>书目名称Machine Learning in Molecular Sciences读者反馈<br> http://impactfactor.cn/2024/5y/?ISSN=BK0620699<br><br> <br><br>书目名称Machine Learning in Molecular Sciences读者反馈学科排名<br> http://impactfactor.cn/2024/5yr/?ISSN=BK0620699<br><br> <br><br>
哑巴
发表于 2025-3-21 21:11:52
Machine Learning in Molecular Sciences978-3-031-37196-7Series ISSN 2542-4491 Series E-ISSN 2542-4483
incisive
发表于 2025-3-22 02:37:21
https://doi.org/10.1007/978-3-031-37196-7Machine Learning; Molecular Sciences; Deep Learning; Artificial Intelligence; Graph Neural Networks; Voxe
essential-fats
发表于 2025-3-22 07:45:05
Development of Exchange-Correlation Functionals Assisted by Machine Learning,ation functionals of density functional theory. In this chapter, we review how the ML tools are used for this and the performances achieved recently. It is revealed that the ML, not being opposed to the analytical methods, complements human intuition and advances the development of the first-principles calculation with desired accuracy.
APNEA
发表于 2025-3-22 09:34:15
Chen Qu,Hanchao LiuComprehensive survey of machine learning in molecular sciences.Perspectives on challenges and future of machine learning in chemistry.Features contributions from experts in the field
变化
发表于 2025-3-22 15:45:54
Challenges and Advances in Computational Chemistry and Physicshttp://image.papertrans.cn/m/image/620699.jpg
POINT
发表于 2025-3-22 18:02:54
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Encumber
发表于 2025-3-22 21:47:53
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大约冬季
发表于 2025-3-23 02:48:37
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打火石
发表于 2025-3-23 05:52:23
Development of Exchange-Correlation Functionals Assisted by Machine Learning,ation functionals of density functional theory. In this chapter, we review how the ML tools are used for this and the performances achieved recently. It is revealed that the ML, not being opposed to the analytical methods, complements human intuition and advances the development of the first-princip