University of Cambridge > Talks.cam > Machine learning in Physics, Chemistry and Materials discussion group (MLDG) > Journal club: Incorporating Electronic Information into Machine Learning Potential Energy Surfaces via Approaching the Ground-State Electronic Energy as a Function of Atom-Based Electronic Populations

Journal club: Incorporating Electronic Information into Machine Learning Potential Energy Surfaces via Approaching the Ground-State Electronic Energy as a Function of Atom-Based Electronic Populations

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If you have a question about this talk, please contact Bingqing Cheng .

The talk will cover “Incorporating Electronic Information into Machine Learning Potential Energy Surfaces via Approaching the Ground-State Electronic Energy as a Function of Atom-Based Electronic Populations” by X. Xie, K. A. Persson and D. W. Small, https://pubs.acs.org/doi/10.1021/acs.jctc.0c00217.

This talk is part of the Machine learning in Physics, Chemistry and Materials discussion group (MLDG) series.

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