High throughput screening with machine learning. - Oleksandr Gurbych; Maksym Druchok; Dzvenymyra Yarish; Sofiya Garkot (CoRR, 2020)

Ensembling machine learning models to boost molecular affinity prediction. - Maksym Druchok; Dzvenymyra Yarish; Sofiya Garkot; Tymofii Yu. Nikolaienko; Oleksandr Gurbych (Comput. Biol. Chem., 2021)

Toward efficient generation, correction, and properties control of unique drug-like structures. - Maksym Druchok; Dzvenymyra Yarish; Oleksandr Gurbych; Mykola Maksymenko (J. Comput. Chem., 2021)

Complex machine learning model needs complex testing: Examining predictability of molecular binding affinity by a graph neural network. - Tymofii Yu. Nikolaienko; Oleksandr Gurbych; Maksym Druchok (J. Comput. Chem., 2022)

Advancing molecular graphs with descriptors for the prediction of chemical reaction yields. - Dzvenymyra Yarish; Sofiya Garkot; Oleksandr O. Grygorenko; Dmytro S. Radchenko; Yurii S. Moroz; Oleksandr Gurbych (J. Comput. Chem., 2023)

LOT: Combining LOB and OHCLV Data for Improved Stock Trading. - Oleksandr Gurbych; Ostap Bodnar (CSIT, 2024)

Filling the Gap in LogP $$ LogP $$ and pK a $$ {pK}_a $$ Evaluation for Saturated Fluorine-Containing Derivatives With Machine Learning. - Oleksandr Gurbych; Petro Pavliuk; Dmytro Krasnienkov; Oleksandr Liashuk; Kostiantyn Melnykov; Oleksandr O. Grygorenko (J. Comput. Chem., 2025)