233 citations · 1.1k across the 115 of their papers we have counts for
144 papers
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…
NAMVIS: Next-Scale Autoregressive Multi-View Image Synthesis
Ramil Khafizov, Ilya Statsenko, Ruslan Rakhimov +3
Sparse-view novel view synthesis is a central problem in 3D content creation, but diffusion-based approaches remain limited by iterative denoising, making multi-view generation exp…
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…
Data Unlearning via Inverse Distillation
Aleksei Leonov, Nikita Kornilov, Zhenhe Zhang +3
Multi-step matching models, including flow and diffusion models, produce high-quality outputs but incur substantial inference costs and may reproduce unwanted components of their t…
Tilted Schrödinger Bridge Matching
Sergei Kholkin, Evgeny Burnaev, Alexander Korotin
Schrödinger bridges provide an entropy-regularized framework and a principled solution for unpaired domain translation. In practice, a pretrained bridge may need to be adapted to h…
Impute-EM: Native Mixed-State Diffusion Models for Heterogeneous Data Imputation
Sergei Kholkin, Kirill Sokolov, Dmitry Baranchuk +2
Missing values are ubiquitous in heterogeneous data mining, where numerical, categorical, and binary variables often coexist. Many imputation methods, especially diffusion-based on…