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Andrey Okhotin

2 accepted papers

2026

GAS: Improving Discretization of Diffusion ODEs via Generalized Adversarial Solver

ICLR 2026poster

While diffusion models achieve state-of-the-art generation quality, they still suffer from computationally expensive sampling. Recent works address this issue with gradient-based optimization methods that distill a few-step ODE diffusion solver from the full sampling process, reducing the number of…

Cited by 0SourcecodeScholar
2023

Star-Shaped Denoising Diffusion Probabilistic Models

NeurIPS 2023poster

Denoising Diffusion Probabilistic Models (DDPMs) provide the foundation for the recent breakthroughs in generative modeling. Their Markovian structure makes it difficult to define DDPMs with distributions other than Gaussian or discrete. In this paper, we introduce Star-Shaped DDPM (SS-DDPM). Its *s…