Adversarial Attacks on Deep Models for Financial Transaction Records. - Ivan Fursov; Matvey Morozov; Nina Kaploukhaya; Elizaveta Kovtun; Rodrigo Rivera-Castro; Gleb Gusev; Dmitry Babaev; Ivan Kireev; Alexey Zaytsev 002; Evgeny Burnaev (KDD, 2021)

Sequence Embeddings Help Detect Insurance Fraud. - Ivan Fursov; Elizaveta Kovtun; Rodrigo Rivera-Castro; Alexey Zaytsev 002; Rasul Khasyanov; Martin Spindler; Evgeny Burnaev (IEEE Access, 2022)

New drugs and stock market: how to predict pharma market reaction to clinical trial announcements. - Semen A. Budennyy; Alexey Kazakov; Elizaveta Kovtun; Leonid Zhukov (CoRR, 2022)

Relationships between patenting trends and research activity for green energy technologies. - Regina Tuganova; Anna Permyakova; Anna Kuznetsova; Karina Rakhmanova; Natalia Monzul; Roman Uvarov; Elizaveta Kovtun; Semen A. Budennyy (CoRR, 2022)

The Battle of Information Representations: Comparing Sentiment and Semantic Features for Forecasting Market Trends. - Andrei Zaichenko; Aleksei Kazakov; Elizaveta Kovtun; Semen A. Budennyy (AIST (Supplement), 2023)

Prediction of Urban Population-Facilities Interactions with Graph Neural Network. - Margarita E. Mishina; Stanislav Sobolevsky; Elizaveta Kovtun; Alexander A. Khrulkov; Alexander Belyi; Semen A. Budennyy; Sergey A. Mityagin (ICCSA (1), 2023)

Label Attention Network for sequential multi-label classification: you were looking at a wrong self-attention. - Elizaveta Kovtun; Galina Boeva; Artem Zabolotnyi; Evgeny Burnaev; Martin Spindler; Alexey Zaytsev 002 (CoRR, 2023)

Hiding Backdoors within Event Sequence Data via Poisoning Attacks. - Elizaveta Kovtun; Alina Ermilova; Dmitry Berestnev; Alexey Zaytsev 002 (CoRR, 2023)

Label Attention Network for Temporal Sets Prediction: You Were Looking at a Wrong Self-Attention. - Elizaveta Kovtun; Galina Boeva; Andrey Shulga; Alexey Zaytsev 002 (ECAI, 2024)

Towards Foundation Time Series Model: To Synthesize Or Not To Synthesize? - Kseniia Kuvshinova; Olga Tsymboi; Alina Kostromina; Dmitry Simakov; Elizaveta Kovtun (CoRR, 2024)