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MLatom

A Package for Atomistic Simulations with Machine Learning

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Home › View all posts by Yaohuang Huang

Author: Yaohuang Huang

Evaluating AIQM1 on Reaction Barrier Heights

By Yaohuang Huang Posted on February 10, 2023 Posted in Featured Publication No Comments Tagged with manual, publication
Evaluating AIQM1 on Reaction Barrier Heights

Yuxinxin Chen, Yanchi Ou, Peikun Zheng, Yaohuang Huang, Fuchun Ge, Pavlo Dral*. Benchmark of General-Purpose Machine Learning-Based Quantum Mechanical Method AIQM1 on Reaction Barrier Heights. J. Chem. Phys. 2023, in press. DOI: 10.1063/5.0137101. Blog post ›

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

  • (p)KREG Models for Accurate Molecular Potential Energy Surfaces
  • WS22 database, Wigner Sampling and geometry interpolation for configurationally diverse molecular datasets
  • Explaining and Predicting Two-Photon Absorption with Machine Learning
  • Evaluating AIQM1 on Reaction Barrier Heights
  • Roundup of MLatom’s Year 2022. What to Expect in 2023?

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