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A Package for Atomistic Simulations with Machine Learning

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Home › View all posts by Fuchun Ge

Author: Fuchun Ge

Speeding up quantum dissipative dynamics of open systems with kernel methods

By Fuchun Ge Posted on March 25, 2022 Posted in Featured Publication No Comments
Speeding up quantum dissipative dynamics of open systems with kernel methods

Arif Ullah, Pavlo O. Dral, Speeding up Quantum Dissipative Dynamics of Open Systems with Kernel Methods. New J. Phys. 2021, 23, 113019. DOI: 10.1088/1367-2630/ac3261. Blog post ›

Benchmarking machine learning potentials

By Fuchun Ge Posted on September 24, 2021 Posted in Featured Publication, News No Comments Tagged with publication, release
Benchmarking machine learning potentials

Max Pinheiro Jr, Fuchun Ge, Nicolas Ferré, Pavlo O. Dral, Mario Barbatti. Choosing the right molecular machine learning potential. Chem. Sci., 2021, 12, 14396–14413. DOI: 10.1039/D1SC03564A. Blog post › | Tutorial ›

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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