Wasserstein GANs Work Because They Fail (to Approximate the Wasserstein Distance). - Jan Stanczuk; Christian Etmann; Lisa Maria Kreusser; Carola-Bibiane Schönlieb (CoRR, 2021)

Conditional Image Generation with Score-Based Diffusion Models. - Georgios Batzolis; Jan Stanczuk; Carola-Bibiane Schönlieb; Christian Etmann (CoRR, 2021)

Classification of datasets with imputed missing values: does imputation quality matter? - Tolou Shadbahr; Michael Roberts; Jan Stanczuk; Julian D. Gilbey; Philip Teare; Sören Dittmer; Matthew Thorpe; Ramón Viñas Torné 001; Evis Sala; Pietro Lió; Mishal Patel; AIX-COVNET Collaboration; et al. (CoRR, 2022)

Non-Uniform Diffusion Models. - Georgios Batzolis; Jan Stanczuk; Carola-Bibiane Schönlieb; Christian Etmann (CoRR, 2022)

Your diffusion model secretly knows the dimension of the data manifold. - Georgios Batzolis; Jan Stanczuk; Carola-Bibiane Schönlieb (CoRR, 2022)

Variational Diffusion Auto-encoder: Deep Latent Variable Model with Unconditional Diffusion Prior. - Georgios Batzolis; Jan Stanczuk; Carola-Bibiane Schönlieb (CoRR, 2023)

Closing the ODE-SDE gap in score-based diffusion models through the Fokker-Planck equation. - Teo Deveney; Jan Stanczuk; Lisa Maria Kreusser; Chris J. Budd; Carola-Bibiane Schönlieb (CoRR, 2023)

Navigating the development challenges in creating complex data systems. - Sören Dittmer; Michael Roberts; Julian D. Gilbey; Ander Biguri; Ian Selby; Anna Breger; Matthew Thorpe; Jonathan R. Weir-McCall; Effrossyni Gkrania-Klotsas; Anna Korhonen; Emily R. Jefferson; Georg Langs; et al. (Nat. Mac. Intell., 2023)

Time Series Diffusion in the Frequency Domain. - Jonathan Crabbé; Nicolas Huynh; Jan Stanczuk; Mihaela van der Schaar (ICML, 2024)

Diffusion Models Encode the Intrinsic Dimension of Data Manifolds. - Jan Stanczuk; Georgios Batzolis; Teo Deveney; Carola-Bibiane Schönlieb (ICML, 2024)