Pavlo O Dral

Quantum Chemistry in the Age of Machine Learning.

Pavlo O. Dral, Pavlo O Dral, 2020, The journal of physical chemistry letters.

Hierarchical machine learning of potential energy surfaces.

Gábor Csányi, Alexey Dral, Pavlo O. Dral, 2020, The Journal of chemical physics.

Structure-based sampling and self-correcting machine learning for accurate calculations of potential energy surfaces and vibrational levels.

Walter Thiel, Pavlo O. Dral, Pavlo O Dral, 2017, The Journal of chemical physics.

MLatom: A program package for quantum chemical research assisted by machine learning

Pavlo O. Dral, Pavlo O Dral, 2019, J. Comput. Chem..

The relationship between threshold voltage and dipolar character of self-assembled monolayers in organic thin-film transistors.

Timo Meyer-Friedrichsen, Andreas Hirsch, Michael Salinas, 2012, Journal of the American Chemical Society.

Deep Learning for Nonadiabatic Excited-State Dynamics.

Wei-Hai Fang, Ganglong Cui, Pavlo O. Dral, 2018, The journal of physical chemistry letters.

Big Data Meets Quantum Chemistry Approximations: The Δ-Machine Learning Approach.

Matthias Rupp, Pavlo O. Dral, Pavlo O Dral, 2015, Journal of chemical theory and computation.

Nonadiabatic Excited-State Dynamics with Machine Learning

Walter Thiel, Mario Barbatti, Pavlo O. Dral, 2018, The journal of physical chemistry letters.