Learning and Scaling Directed Networks via Graph Embedding. - Mikhail Drobyshevskiy; Anton Korshunov; Denis Turdakov (ECML/PKDD (1), 2017)

Methods for Information Diffusion Analysis. - A. A. Avetisyan; Mikhail Drobyshevskiy; D. Yu. Turdakov; Tsolak Ghukasyan (Program. Comput. Softw., 2019)

Random Graph Modeling: A Survey of the Concepts. - Mikhail Drobyshevskiy; Denis Turdakov (ACM Comput. Surv., 2020)

Context Specificity Matters: Profile Attributes Prediction for Social Network Users. - Andrey Gomzin; Mikhail Drobyshevskiy; Denis Turdakov (CISS, 2021)

AADMIP: Adversarial Attacks and Defenses Modeling in Industrial Processes. - Vitaliy Pozdnyakov; Aleksandr Kovalenko; Ilya Makarov; Mikhail Drobyshevskiy; Kirill Lukyanov (IJCAI, 2024)

Adversarial Attacks and Defenses in Automated Control Systems: A Comprehensive Benchmark. - Vitaliy Pozdnyakov; Aleksandr Kovalenko; Ilya Makarov; Mikhail Drobyshevskiy; Kirill Lukyanov (CoRR, 2024)

Graph Neural Network for Crawling Target Nodes in Social Networks. - Kirill Lukyanov; Mikhail Drobyshevskiy; Danil Shaikhelislamov; Denis Turdakov (CoRR, 2024)

Collecting Influencers: A Comparative Study of Online Network Crawlers. - Mikhail Drobyshevskiy; Denis Aivazov; Denis Turdakov; Alexander Yatskov; Maksim Varlamov; Danil Shayhelislamov (CoRR, 2024)

Framework GNN-AID: Graph Neural Network Analysis Interpretation and Defense. - Kirill Lukyanov; Mikhail Drobyshevskiy; Georgii Sazonov; Mikhail Soloviov; Ilya Makarov (CoRR, 2025)