1 citations · 2 across the 32 of their papers we have counts for
4 papers · 1 filter
On the Equivalence of Optimal Transport Problem and Action Matching with Optimal Vector Fields
Nikita Kornilov, Alexander Korotin
Flow Matching (FM) method in generative modeling maps arbitrary probability distributions by constructing an interpolation between them and then learning the vector field that defi…
Universal Inverse Distillation for Matching Models with Real-Data Supervision (No GANs)
Nikita Kornilov, David Li, Tikhon Mavrin +5
While achieving exceptional generative quality, modern diffusion, flow, and other matching models suffer from slow inference, as they require many steps of iterative generation. Re…
Robust Barycenter Estimation using Semi-Unbalanced Neural Optimal Transport
Milena Gazdieva, Jaemoo Choi, Alexander Kolesov +3
Aggregating data from multiple sources can be formalized as an Optimal Transport (OT) barycenter problem, which seeks to compute the average of probability distributions with respe…
Optimal Flow Matching: Learning Straight Trajectories in Just One Step
Nikita Kornilov, Petr Mokrov, Alexander Gasnikov +1
Over the several recent years, there has been a boom in development of Flow Matching (FM) methods for generative modeling. One intriguing property pursued by the community is the a…