3 papers
cs.LG2025
MiAD: Mirage Atom Diffusion for De Novo Crystal Generation
Andrey Okhotin, Maksim Nakhodnov, Nikita Kazeev +3
In recent years, diffusion-based models have demonstrated exceptional performance in searching for simultaneously stable, unique, and novel (S.U.N.) crystalline materials. However,…
cs.CV2025
GAS: Improving Discretization of Diffusion ODEs via Generalized Adversarial Solver
Aleksandr Oganov, Ilya Bykov, Eva Neudachina +7
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 o…
stat.ML2023
Star-Shaped Denoising Diffusion Probabilistic Models
Andrey Okhotin, Dmitry Molchanov, Vladimir Arkhipkin +4
Denoising Diffusion Probabilistic Models (DDPMs) provide the foundation for the recent breakthroughs in generative modeling. Their Markovian structure makes it difficult to define…