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A Package for Atomistic Simulations with Machine Learning

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Home › View all posts by Yaohuang Huang

Author: Yaohuang Huang

A comparative study of different machine learning methods for dissipative quantum dynamics

By Yaohuang Huang Posted on October 19, 2022 Posted in Featured Publication No Comments
A comparative study of different machine learning methods for dissipative quantum dynamics

Luis E. Herrera Rodríguez, Arif Ullah, Kennet J. Rueda Espinosa, Pavlo O. Dral*, Alexei A. Kananenka*. A comparative study of different machine learning methods for dissipative quantum dynamics. Mach. Learn. Sci. Technol. 2022, 3, 045016. DOI: 10.1088/2632-2153/ac9a9d. Blog post › 

News & Posts

  • Roundup of MLatom’s Year 2022. What to Expect in 2023?
  • New manual for MLatom@XACS
  • A comparative study of different machine learning methods for dissipative quantum dynamics
  • The Newton-X platform for surface hopping and nuclear ensembles
  • Book “Quantum Chemistry in the Age of Machine Learning”

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