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Home › View all posts by Pavlo Dral

Author: Pavlo Dral

Chapter on Machine Learning in Quantum Chemistry in a Tutorial Way

By Pavlo Dral Posted on September 22, 2020 Posted in Uncategorized No Comments
Chapter on Machine Learning in Quantum Chemistry in a Tutorial Way

Pavlo O. Dral, Quantum Chemistry Assisted by Machine Learning. In Advances in Quantum Chemistry: Chemical Physics and Quantum Chemistry, Volume 81, 1st ed.; Kenneth Ruud, Erkki J. Brändas, Eds. Academic Press: 2020; Vol. 81. Read more ›

MLatom 1.1

By Pavlo Dral Posted on March 30, 2020 Posted in News 2 Comments Tagged with , release
MLatom 1.1

MLatom 1.1 is released. Read more ›

Paper on MLatom

By Pavlo Dral Posted on June 25, 2019 Posted in Featured Publication, News No Comments
Paper on MLatom

P. O. Dral, MLatom: A Program Package for Quantum Chemical Research Assisted by Machine Learning. J. Comput. Chem. 2019, 40, 2339–2347. DOI: 10.1002/jcc.26004. Read more ›

MLatom 1.0

By Pavlo Dral Posted on April 19, 2019 Posted in News No Comments Tagged with , release
MLatom 1.0

MLatom 1.0 release is now available. Read more ›

Machine Learning Accelerates Excited-State Dynamics

By Pavlo Dral Posted on September 14, 2018 Posted in Featured Publication, News No Comments
Machine Learning Accelerates Excited-State Dynamics

P. O. Dral, M. Barbatti, W. Thiel, Nonadiabatic Excited-State Dynamics with Machine Learning. J. Phys. Chem. Lett. 2018, 9, 5660–5663. Read more ›

Self-Correcting Machine Learning and Structure-Based Sampling

By Pavlo Dral Posted on May 20, 2018 Posted in Featured Publication, News No Comments
Self-Correcting Machine Learning and Structure-Based Sampling

P. O. Dral, A. Owens, S. N. Yurchenko, W. Thiel, Structure-Based Sampling and Self-Correcting Machine Learning for Accurate Calculations of Potential Energy Surfaces and Vibrational Levels. J. Chem. Phys. 2017, 146, 244108. Read more ›

Correcting Differences with Machine Learning

By Pavlo Dral Posted on May 20, 2018 Posted in Featured Publication, News No Comments
Correcting Differences with Machine Learning

R. Ramakrishnan, P. O. Dral, M. Rupp, O. A. von Lilienfeld, Big Data Meets Quantum Chemistry Approximations: The Δ-Machine Learning Approach. J. Chem. Theory Comput. 2015, 11, 2087–2096. Read more ›

Machine Learning of Semiempirical Parameters

By Pavlo Dral Posted on May 20, 2018 Posted in Featured Publication, News No Comments
Machine Learning of Semiempirical Parameters

P. O. Dral, O. A. von Lilienfeld, W. Thiel, Machine Learning of Parameters for Accurate Semiempirical Quantum Chemical Calculations. J. Chem. Theory Comput. 2015, 11, 2120–2125. Read more ›

News & Posts

  • MLatom 1.2: ML absorption spectra
  • Chapter on Machine Learning in Quantum Chemistry in a Tutorial Way
  • MLatom 1.1
  • Paper on MLatom
  • MLatom 1.0

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