InDiD: Instant Disorder Detection via a Principled Neural Network. - Evgenia Romanenkova; Alexander Stepikin; Matvey Morozov; Alexey Zaytsev 002 (ACM Multimedia, 2022)

Deep learning model solves change point detection for multiple change types. - Alexander Stepikin; Evgenia Romanenkova; Alexey Zaytsev 002 (CoRR, 2022)

Continuous-time convolutions model of event sequences. - Vladislav Zhuzhel; Vsevolod Grabar; Galina Boeva; Artem Zabolotnyi; Alexander Stepikin; Vladimir Zholobov; Maria Ivanova; Mikhail Orlov; Ivan Kireev; Evgeny Burnaev; Rodrigo Rivera-Castro; Alexey Zaytsev 002 (CoRR, 2023)

Universal representations for financial transactional data: embracing local, global, and external contexts. - Alexandra Bazarova; Maria Kovaleva; Ilya Kuleshov; Evgenia Romanenkova; Alexander Stepikin; Alexandr Yugay; Dzhambulat Mollaev; Ivan Kireev; Andrey V. Savchenko; Alexey Zaytsev 002 (CoRR, 2024)

Learning transactions representations for information management in banks: Mastering local, global, and external knowledge. - Alexandra Bazarova; Maria Kovaleva; Ilya Kuleshov; Evgenia Romanenkova; Alexander Stepikin; Aleksandr Yugay; Dzhambulat Mollaev; Ivan Kireev; Andrey V. Savchenko; Alexey Zaytsev 002 (Int. J. Inf. Manag. Data Insights, 2025)

WWAggr: A Window Wasserstein-based Aggregation for Ensemble Change Point Detection. - Alexander Stepikin; Evgenia Romanenkova; Alexey Zaytsev 002 (CoRR, 2025)