Showing results (1-10 of 17) with videos related to
Sort By:
Pageof 2
Scientific Reports|September 2, 2022
A universal similarity based approach for predictive uncertainty quantification in materials scienceVadim Korolev, Iurii Nevolin, Pavel ProtsenkoPatterns (New York, N.Y.)|October 25, 2023
Accurate, interpretable predictions of materials properties within transformer language modelsVadim Korolev, Pavel ProtsenkoInorganic Chemistry|June 23, 2025
Structure and Thermal Stability of Carbohydrazide Complexes with Uranium(VI) Nitrate, Perrhenate, Perchlorate, and ChlorideEvgeny Gerber, Alexei Bessonov, Mikhail Grigoriev, et al.Iscience|April 17, 2024
The carbon footprint of predicting CO2 storage capacity in metal-organic frameworks within neural networksVadim Korolev, Artem MitrofanovJournal of Chemical Information and Modeling|March 8, 2024
Coarse-Grained Crystal Graph Neural Networks for Reticular Materials DesignVadim Korolev, Artem MitrofanovPhysical Chemistry Chemical Physics : PCCP|October 7, 2024
Carbon materials for effective purification of aqueous solutions from tributyl phosphateTamuna Bakhiia, Andrey Toropov, Iurii Nevolin, et al.The Journal of Physical Chemistry. A|December 4, 2024
Experimental and Theoretical X-ray Absorption Near Edge Structure Study of UO Systems at the U L3 EdgeDaniil Novichkov, Tatiana Poliakova, Iurii Nevolin, et al.Journal of Synchrotron Radiation|September 22, 2023
Laboratory-based X-ray spectrometer for actinide scienceDaniil Novichkov, Alexander Trigub, Evgeny Gerber, et al.Journal of Chemical Information and Modeling|December 23, 2025
gSelformer-MV: Multiview, Subgraph-Augmented Group SELFIES Transformer for Molecular Property PredictionVadim Korolev, Alexey Andreevich Sorokin, Yuri KuratovJournal of Chemical Information and Modeling|December 21, 2019
Graph Convolutional Neural Networks as "General-Purpose" Property Predictors: The Universality and Limits of ApplicabilityVadim Korolev, Artem Mitrofanov, Alexandru Korotcov, et al.Pageof 2