Zobrazeno 1 - 10
of 6 312
pro vyhledávání: '"Kolesov, A."'
Publikováno v:
Известия высших учебных заведений: Прикладная нелинейная динамика, Vol 32, Iss 3, Pp 376-393 (2024)
The purpose of this work is to study a new mathematical model of a ring neural network with unidirectional chemical connections, which is a singularly perturbed system of differential-difference equations with delay. Methods. A combination of analyti
Externí odkaz:
https://doaj.org/article/5a0817470384445298f0e56e0f6a4133
Publikováno v:
Известия высших учебных заведений: Прикладная нелинейная динамика, Vol 30, Iss 2, Pp 152-175 (2022)
The purpose of this work is to study the dynamic properties of solutions to special systems of ordinary differential equations, called fully connected networks of nonlinear oscillators. Methods. A new approach to obtain periodic regimes of the chimer
Externí odkaz:
https://doaj.org/article/03c69be4aa7b45fb8a8a73da910d1c13
Autor:
Kolesov, Grigory
In the laser processing of glass, a ~50-1000 $\mu$m-thick layer of glass is heated to a high temperature by the laser beam. Due to the shallow depth of this hot layer, the infrared emission and absorption spectra may deviate from the black-body spect
Externí odkaz:
http://arxiv.org/abs/2412.10561
Autor:
Gazdieva, Milena, Choi, Jaemoo, Kolesov, Alexander, Choi, Jaewoong, Mokrov, Petr, Korotin, Alexander
A common challenge in aggregating data from multiple sources can be formalized as an \textit{Optimal Transport} (OT) barycenter problem, which seeks to compute the average of probability distributions with respect to OT discrepancies. However, the pr
Externí odkaz:
http://arxiv.org/abs/2410.03974
Publikováno v:
Известия высших учебных заведений: Прикладная нелинейная динамика, Vol 29, Iss 5, Pp 775-798 (2021)
Nonlinear systems of differential equations with delay, which are mathematical models of fully connected networks of impulse neurons, are considered. Purpose of this work is to study the dynamic properties of one special class of solutions to these s
Externí odkaz:
https://doaj.org/article/4d211ccf80174a41971a6c83a6c0a9b0
Autor:
Kolesov, Alexander, Mokrov, Petr, Udovichenko, Igor, Gazdieva, Milena, Pammer, Gudmund, Burnaev, Evgeny, Korotin, Alexander
Given a collection of probability measures, a practitioner sometimes needs to find an "average" distribution which adequately aggregates reference distributions. A theoretically appealing notion of such an average is the Wasserstein barycenter, which
Externí odkaz:
http://arxiv.org/abs/2402.03828
Autor:
Kolesov, Alexander, Mokrov, Petr, Udovichenko, Igor, Gazdieva, Milena, Pammer, Gudmund, Kratsios, Anastasis, Burnaev, Evgeny, Korotin, Alexander
Optimal transport (OT) barycenters are a mathematically grounded way of averaging probability distributions while capturing their geometric properties. In short, the barycenter task is to take the average of a collection of probability distributions
Externí odkaz:
http://arxiv.org/abs/2310.01105
Autor:
Yi Gao, Xiaohui Chen, Qinzhu Yang, Andras Lasso, Ivan Kolesov, Steve Pieper, Ron Kikinis, Allen Tannenbaum, Liangjia Zhu
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-19 (2024)
Abstract 3D medical image segmentation is a key step in numerous clinical applications. Even though many automatic segmentation solutions have been proposed, it is arguably that medical image segmentation is more of a preference than a reference as i
Externí odkaz:
https://doaj.org/article/6368e324b34f4f2ea90c1551e3a0bac6
Autor:
Gushchin, Nikita, Kolesov, Alexander, Mokrov, Petr, Karpikova, Polina, Spiridonov, Andrey, Burnaev, Evgeny, Korotin, Alexander
Over the last several years, there has been significant progress in developing neural solvers for the Schr\"odinger Bridge (SB) problem and applying them to generative modelling. This new research field is justifiably fruitful as it is interconnected
Externí odkaz:
http://arxiv.org/abs/2306.10161
Energy-based models (EBMs) are known in the Machine Learning community for decades. Since the seminal works devoted to EBMs dating back to the noughties, there have been a lot of efficient methods which solve the generative modelling problem by means
Externí odkaz:
http://arxiv.org/abs/2304.06094