Towards a Better Understanding of Deep Neural Networks Representations using Deep Generative Networks. - Jérémie Despraz; Stéphane Gomez; Héctor F. Satizábal; Carlos Andrés Peña-Reyes (IJCCI, 2017)

Exploring Internal Representations of Deep Neural Networks. - Jérémie Despraz; Stéphane Gomez; Héctor F. Satizábal; Carlos Andrés Peña-Reyes (IJCCI (Selected Papers), 2017)

Deep Learning on Retina Images as Screening Tool for Diagnostic Decision Support. - Maria Camila Alvarez Trivino; Jérémie Despraz; Jesús Alfonso López Sotelo; Carlos Andrés Peña (CoRR, 2018)

Generation and Evaluation of Synthetic Data in a University Hospital Setting. - Bayrem Kaabachi; Jérémie Despraz; Thierry Meurers; Fabian Prasser; Jean Louis Raisaro (MIE, 2022)

Tunable Privacy Risk Evaluation of Generative Adversarial Networks. - Bogdan Kulynych; Jérémie Despraz; Jean Louis Raisaro (MIE, 2024)

Evaluating Synthetic Data Augmentation to Correct for Data Imbalance in Realistic Clinical Prediction Settings. - Bogdan Kulynych; Jérémie Despraz; Christian Simon; Jean Louis Raisaro (MIE, 2024)

Phantom Anonymization: Adversarial testing for membership inference risks in anonymized health data. - Thierry Meurers; Mehmed Halilovic; Karen Otte; Jérémie Despraz; Bayrem Kaabachi; Bogdan Kulynych; Jean Louis Raisaro; Fabian Prasser (Comput. Biol. Medicine, 2025)

A scoping review of privacy and utility metrics in medical synthetic data. - Bayrem Kaabachi; Jérémie Despraz; Thierry Meurers; Karen Otte; Mehmed Halilovic; Bogdan Kulynych; Fabian Prasser; Jean Louis Raisaro (npj Digit. Medicine, 2025)

A quantitative analysis of the use of anonymization in biomedical research. - Thierry Meurers; Karen Otte; Hammam Abu Attieh; Farah Briki; Jérémie Despraz; Mehmed Halilovic; Bayrem Kaabachi; Vladimir Milicevic; Armin Müller; Grigorios Papapostolou; Felix Nikolaus Wirth; Jean Louis Raisaro; et al. (npj Digit. Medicine, 2025)