activity
20182024
most citedInDiD: Instant Disorder Detection via Representation Learning

6 citations · 10 across the 4 of their papers we have counts for

collaborators

7 papers

cs.LG2024★ 4 cited

Learning Transactions Representations for Information Management in Banks: Mastering Local, Global, and External Knowledge

Alexandra Bazarova, Maria Kovaleva, Ilya Kuleshov +7

In today's world, banks use artificial intelligence to optimize diverse business processes, aiming to improve customer experience. Most of the customer-related tasks can be categor…

cs.LG2022

Usage of specific attention improves change point detection

Anna Dmitrienko, Evgenia Romanenkova, Alexey Zaytsev

The change point is a moment of an abrupt alteration in the data distribution. Current methods for change point detection are based on recurrent neural methods suitable for sequent…

cs.LG2022

Deep learning model solves change point detection for multiple change types

Alexander Stepikin, Evgenia Romanenkova, Alexey Zaytsev

A change points detection aims to catch an abrupt disorder in data distribution. Common approaches assume that there are only two fixed distributions for data: one before and anoth…

cs.LG2021★ 6 cited

InDiD: Instant Disorder Detection via Representation Learning

Evgenia Romanenkova, Alexander Stepikin, Matvey Morozov +1

For sequential data, a change point is a moment of abrupt regime switch in data streams. Such changes appear in different scenarios, including simpler data from sensors and more ch…

cs.LG2019

Application of Machine Learning to accidents detection at directional drilling

Ekaterina Gurina, Nikita Klyuchnikov, Alexey Zaytsev +5

We present a data-driven algorithm and mathematical model for anomaly alarming at directional drilling. The algorithm is based on machine learning. It compares the real-time drilli…

cs.LG2019

Real-time data-driven detection of the rock type alteration during a directional drilling

Evgenya Romanenkova, Alexey Zaytsev, Nikita Klyuchnikov +8

During the directional drilling, a bit may sometimes go to a nonproductive rock layer due to the gap about 20m between the bit and high-fidelity rock type sensors. The only way to…