Innovative Non-parametric Texture Synthesis via Patch Permutations. - Ryan Webster (CoRR, 2018)

Detecting Overfitting of Deep Generative Networks via Latent Recovery. - Ryan Webster; Julien Rabin; Loïc Simon; Frédéric Jurie (CVPR, 2019)

Revisiting precision recall definition for generative modeling. - Loïc Simon; Ryan Webster; Julien Rabin (ICML, 2019)

Revisiting Precision and Recall Definition for Generative Model Evaluation. - Loïc Simon; Ryan Webster; Julien Rabin (CoRR, 2019)

Generating Private Data Surrogates for Vision Related Tasks. - Ryan Webster; Julien Rabin; Loïc Simon; Frédéric Jurie (ICPR, 2020)

Equivalence of several curves assessing the similarity between probability distributions. - Loïc Simon; Julien Rabin; Ryan Webster (CoRR, 2020)

This Person (Probably) Exists. Identity Membership Attacks Against GAN Generated Faces. - Ryan Webster; Julien Rabin; Loïc Simon; Frédéric Jurie (CoRR, 2021)

Width-Wise Parameter Sharing for Multi-Domain Gan Learning. - Ryan Webster; Julien Rabin; Loïc Simon; Frédéric Jurie (ICIP, 2022)

On the De-duplication of LAION-2B. - Ryan Webster; Julien Rabin; Loïc Simon; Frédéric Jurie (CoRR, 2023)

A Reproducible Extraction of Training Images from Diffusion Models. - Ryan Webster (CoRR, 2023)

On the Theoretical Equivalence of Several Trade-Off Curves Assessing Statistical Proximity. - Rodrigue Siry; Ryan Webster; Loïc Simon; Julien Rabin (J. Mach. Learn. Res., 2023)

Evaluation of Deep Image Generation Through the Lens of Privacy and Utility. (Evaluation de la synthèse d'images au travers du prisme de la confidentialité). - Ryan Webster (2023)