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physics.comp-ph2019
Graph convolutional neural networks as "general-purpose" property predictors: the universality and limits of applicability
Vadim Korolev, Artem Mitrofanov, Alexandru Korotcov +1
Nowadays the development of new functional materials/chemical compounds using machine learning (ML) techniques is a hot topic and includes several crucial steps, one of which is th…
physics.comp-ph2019
Transferable and extensible machine learning derived atomic charges for modeling hybrid nanoporous materials
Vadim Korolev, Artem Mitrofanov, Ekaterina Marchenko +3
Nanoporous materials have attracted significant interest as an emerging platform for adsorption-related applications. The high-throughput computational screening became a standard…