Jingbai LiAssociate ProfessorDevelopments and applications of machine learning nonadiabatic molecular dynamics Jingbai Li, associate professor of HIAM at Shenzhen Polytechnic. Jingbai received his B.S. from Zhengzhou University in China and his Ph.D. from the Department of Chemistry at the Illinois ...
本文将从PHAS0077: Scientific Computing Individual Research Project 2021/22 Projects 中摘选 Machine Learning相关的课题供选择,并对Summary内容做机翻以供快速参考。文中涉及到的Supervisor信息 均未给出,…
Finally, from a hands-on experience from several ongoing medicinal chemistry projects at Novartis, MolSkill is currently being applied in several routine tasks. Specifically, in an era where machine-learning methods can design tens of thousands of compounds, or technologies such as high-throughput sc...
FAIR Chemistry's library of machine learning methods for chemistry - GitHub - FAIR-Chem/fairchem: FAIR Chemistry's library of machine learning methods for chemistry
Machine learning has rapidly become a pivotal tool across the chemical and pharmaceutical sciences, revolutionizing our approach to research and discovery. This Collection aims to explore the wide-ranging applications of machine learning in chemistry, encompassing drug development, materials science, chemical...
We discuss the elements necessary to train reliable, repeatable and reproducible models, and recommend a set of guidelines for machine learning reports.doi:10.1038/s41557-021-00716-zNat ChemNature chemistry
Machine learning algorithms have been employed to speed up the discovery, synthesis, and optimization of materials and chemicals. In this special issue, iScience and Trends in Chemistry bring together a collection of review and research articles in this interdisciplinary field, guest edited by Dr. Ra...
Machine learning tools for Chemistry. Contribute to CheML/CheML development by creating an account on GitHub.
期待申请者加入后开展如下科研任务中的部分工作：- 进行基于Machine learning（ML）的建模、决策控制...
Machine learning in materials chemistry: an invitation Mach. Learn. Appl. (2022) L.E. Vivanco-Benavides et al. Machine learning and materials informatics approaches in the analysis of physical properties of carbon nanotubes: a review Comput. Mater. Sci. (2022) Y. Liu et al. Machine learning...