collaborators

5 papers

cs.LG2026

Interaction Field Matching: Overcoming Limitations of Electrostatic Models

Stepan I. Manukhov, Alexander Kolesov, Vladimir V. Palyulin +1

Electrostatic field matching (EFM) has recently appeared as a novel physics-inspired paradigm for data generation and transfer using the idea of an electric capacitor. However, it…

cs.LG2025

Electric Currents for Discrete Data Generation

Alexander Kolesov, Stepan Manukhov, Vladimir V. Palyulin +1

We propose lectric urrent iscrete ata eneration (ECDG), a pioneering method for data generation in discrete settin…

cs.LG2025

Field Matching: an Electrostatic Paradigm to Generate and Transfer Data

Alexander Kolesov, Manukhov Stepan, Vladimir V. Palyulin +1

We propose Electrostatic Field Matching (EFM), a novel method that is suitable for both generative modeling and distribution transfer tasks. Our approach is inspired by the physics…

stat.ML2025

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…

cs.LG2025

Energy-Guided Continuous Entropic Barycenter Estimation for General Costs

Alexander Kolesov, Petr Mokrov, Igor Udovichenko +5

Optimal transport (OT) barycenters are a mathematically grounded way of averaging probability distributions while capturing their geometric properties. In short, the barycenter tas…