1 citations · 1 across the 6 of their papers we have counts for
Showing 2026Show all
2 papers · 1 filter
cs.LG2026
CLaST: Context-aware Contrastive VAE for Probabilistic Time Series Forecasting
Alexander Marusov, Dmitry Anikin, Petr Sokerin +3
Probabilistic forecasting models are widely used for time series forecasting in domains such as energy systems, finance, medicine, and transportation. In recent years, deep generat…
cs.LG2026
GENADA: efficient generative time series adversarial attack framework
Michael Baronov, Denis Vorobev, Margarita Rusanova +2
Deep learning models are widely used for time series analysis in domains such as healthcare, finance, energy systems, and environmental monitoring. However, these models remain vul…