Toward privacy in IoT mobile devices for activity recognition. - Théo Jourdan; Antoine Boutet; Carole Frindel (MobiQuitous, 2018)

Motion sensor data anonymization by time-frequency filtering. - Noëlie Debs; Théo Jourdan; Ali Moukadem; Antoine Boutet; Carole Frindel (EUSIPCO, 2020)

DYSAN: Dynamically sanitizing motion sensor data against sensitive inferences through adversarial networks. - Antoine Boutet; Carole Frindel; Sébastien Gambs; Théo Jourdan; Claude Rosin Ngueveu (CoRR, 2020)

DySan: Dynamically Sanitizing Motion Sensor Data Against Sensitive Inferences through Adversarial Networks. - Antoine Boutet; Carole Frindel; Sébastien Gambs; Théo Jourdan; Rosin Claude Ngueveu (AsiaCCS, 2021)

Privacy Assessment of Federated Learning Using Private Personalized Layers. - Théo Jourdan; Antoine Boutet; Carole Frindel (MLSP, 2021)

Privacy-preserving IoT Framework for Activity Recognition in Personal Healthcare Monitoring. - Théo Jourdan; Antoine Boutet; Amine Bahi; Carole Frindel (ACM Trans. Comput. Heal., 2021)

The Contribution of Machine Learning in the Validation of Commercial Wearable Sensors for Gait Monitoring in Patients: A Systematic Review. - Théo Jourdan; Noëlie Debs; Carole Frindel (Sensors, 2021)

Privacy and transparency in learning systems for healthcare. (Protection de la vie privée dans les systèmes d'apprentissage pour le domaine de la santé). - Théo Jourdan (2021)

Machine Learning for Musical Expression: A Systematic Literature Review. - Théo Jourdan; Baptiste Caramiaux (NIME, 2023)

Culture and Politics of Machine Learning in NIME: A Preliminary Qualitative Inquiry. - Théo Jourdan; Baptiste Caramiaux (NIME, 2023)