$(1 + varepsilon)$-class Classification: an Anomaly Detection Method for Highly Imbalanced or Incomplete Data Sets. - Maxim Borisyak; Artem Ryzhikov; Andrey Ustyuzhanin; Denis Derkach; Fedor Ratnikov; Olga Mineeva (CoRR, 2019)

DeepMAsED: evaluating the quality of metagenomic assemblies. - Olga Mineeva; Mateo Rojas-Carulla; Ruth E. Ley; Bernhard Schölkopf; Nicholas D. Youngblut (Bioinform., 2020)

(1 + epsilon)-class Classification: an Anomaly Detection Method for Highly Imbalanced or Incomplete Data Sets. - Maxim Borisyak; Artem Ryzhikov; Andrey Ustyuzhanin; Denis Derkach; Fedor Ratnikov; Olga Mineeva (J. Mach. Learn. Res., 2020)

Don't Throw it Away! The Utility of Unlabeled Data in Fair Decision Making. - Miriam Rateike; Ayan Majumdar; Olga Mineeva; Krishna P. Gummadi; Isabel Valera (FAccT, 2022)

Empirical Studies of Everyday Professional, Domestic and Client-Service Communication for the Development of Voice Assistants in Russian. - Tatiana Y. Sherstinova; Irina Petrova 001; Olga Mineeva; Maria Fedosova (FRUCT, 2022)

ResMiCo: Increasing the quality of metagenome-assembled genomes with deep learning. - Olga Mineeva; Daniel Danciu; Bernhard Schölkopf; Ruth E. Ley; Gunnar Rätsch; Nicholas D. Youngblut (PLoS Comput. Biol., 2023)

FAMEWS: a Fairness Auditing tool for Medical Early-Warning Systems. - Marine Hoche; Olga Mineeva; Manuel Burger; Alessandro Blasimme; Gunnar Rätsch (CHIL, 2024)