18 citations · 98 across the 27 of their papers we have counts for
4 papers · 1 filter
Realism VS Accuracy: Event Sequence Forecasting from a Generative Modeling Perspective
Dmitry Osin, Egor Surkov, Petr Mokrov +5
Event sequences are chains of random events, each described by heterogeneous (numerical and categorical) features. The problem of event sequence forecasting occurs in finance, heal…
Light Entropic Optimal Transport on Riemannian Manifolds
Xavier Aramayo-Carrasco, Petr Mokrov, Alexander Korotin
Entropic Optimal Transport (EOT) has become a practical framework for learning stochastic couplings between complex distributions, with applications in generative modeling and doma…
Simultaneous Neural Optimal Transport
Milena Gazdieva, Kirill Sokolov, Jiawei Chen +2
Optimal Transport (OT) provides a principled framework for learning transformations between probability distributions from unpaired samples. In many applications, however, a single…
Rethinking Pixel Mean Flows via Interval Denoiser
Alexander Zaytsev, Dmitry Baranchuk, Alexander Korotin +1
Modern diffusion and flow-based models are increasingly moving toward few-step, latent-free generation to bypass the computational overhead of multi-step sampling and the reconstru…