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cs.LG2026
U-Former ODE: Fast Probabilistic Forecasting of Irregular Time Series
Ilya Kuleshov, Alexander Marusov, Alexey Zaytsev
Probabilistic forecasting of irregularly sampled time series is crucial in domains such as healthcare and finance, yet it remains a formidable challenge. Existing Neural Controlled…
cs.LG2025
A theoretical framework for self-supervised contrastive learning for continuous dependent data
Alexander Marusov, Aleksandr Yugay, Alexey Zaytsev
Self-supervised learning (SSL) has emerged as a powerful approach to learning representations, particularly in the field of computer vision. However, its application to dependent d…
cs.LG2024
Long-term drought prediction using deep neural networks based on geospatial weather data
Alexander Marusov, Vsevolod Grabar, Yury Maximov +3
The problem of high-quality drought forecasting up to a year in advance is critical for agriculture planning and insurance. Yet, it is still unsolved with reasonable accuracy due t…