3 citations · 3 across the 3 of their papers we have counts for
5 papers
Discrete diffusion samplers and bridges: Off-policy algorithms and applications in latent spaces
Arran Carter, Sanghyeok Choi, Kirill Tamogashev +2
Sampling from a distribution known up to a normalising constant is an important and challenging problem in statistics. Recent years have seen the…
Multi-Marginal Flow Matching with Adversarially Learnt Interpolants
Oskar Kviman, Kirill Tamogashev, Nicola Branchini +3
Learning the dynamics of a process given sampled observations at several time points is an important but difficult task in many scientific applications. When no ground-truth trajec…
Data-to-Energy Stochastic Dynamics
Kirill Tamogashev, Esmeralda S. Whitammer
The Schrödinger bridge problem is concerned with finding a stochastic dynamical system bridging two marginal distributions that minimises a certain transportation cost. This proble…
Adaptive Destruction Processes for Diffusion Samplers
Timofei Gritsaev, Nikita Morozov, Kirill Tamogashev +5
This paper explores the challenges and benefits of a trainable destruction process in diffusion samplers -- diffusion-based generative models trained to sample an unnormalised dens…
FINALLY: fast and universal speech enhancement with studio-like quality
Nicholas Babaev, Kirill Tamogashev, Azat Saginbaev +6
In this paper, we address the challenge of speech enhancement in real-world recordings, which often contain various forms of distortion, such as background noise, reverberation, an…