6 papers
WWAggr: A Window Wasserstein-based Aggregation for Ensemble Change Point Detection
Alexander Stepikin, Evgenia Romanenkova, Alexey Zaytsev
Change Point Detection (CPD) aims to identify moments of abrupt distribution shifts in data streams. Real-world high-dimensional CPD remains challenging due to data pattern complex…
Normalizing self-supervised learning for provably reliable Change Point Detection
Alexandra Bazarova, Evgenia Romanenkova, Alexey Zaytsev
Change point detection (CPD) methods aim to identify abrupt shifts in the distribution of input data streams. Accurate estimators for this task are crucial across various real-worl…
Holistic Uncertainty Estimation For Open-Set Recognition
Leonid Erlygin, Alexey Zaytsev
Accurate uncertainty estimation is a critical challenge in open-set recognition, where a probe biometric sample may belong to an unknown identity. It can be addressed through sampl…
DeNOTS: Stable Deep Neural ODEs for Time Series
Ilya Kuleshov, Evgenia Romanenkova, Vladislav Zhuzhel +3
Neural CDEs provide a natural way to process the temporal evolution of irregular time series. The number of function evaluations (NFE) is these systems' natural analog of depth (th…
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…
From Variability to Stability: Advancing RecSys Benchmarking Practices
Valeriy Shevchenko, Nikita Belousov, Alexey Vasilev +6
In the rapidly evolving domain of Recommender Systems (RecSys), new algorithms frequently claim state-of-the-art performance based on evaluations over a limited set of arbitrarily…