DP-CGAN: Differentially Private Synthetic Data and Label Generation. - Reihaneh Torkzadehmahani; Peter Kairouz; Benedict Paten (CVPR Workshops, 2019)

Privacy-preserving Artificial Intelligence Techniques in Biomedicine. - Reihaneh Torkzadehmahani; Reza Nasirigerdeh; David B. Blumenthal; Tim Kacprowski; Markus List; Julian O. Matschinske; Julian Späth; Nina Kerstin Wenke; Béla Bihari; Tobias Frisch; Anne Hartebrodt; Anne-Christin Hauschild; et al. (CoRR, 2020)

Federated Multi-Mini-Batch: An Efficient Training Approach to Federated Learning in Non-IID Environments. - Mohammad Bakhtiari; Reza Nasirigerdeh; Reihaneh Torkzadehmahani; Amirhossein Bayat; David B. Blumenthal; Markus List; Jan Baumbach (CoRR, 2020)

On the Privacy of Federated Pipelines. - Reza Nasirigerdeh; Reihaneh Torkzadehmahani; Jan Baumbach; David B. Blumenthal (SIGIR, 2021)

The FeatureCloud AI Store for Federated Learning in Biomedicine and Beyond. - Julian O. Matschinske; Julian Späth; Reza Nasirigerdeh; Reihaneh Torkzadehmahani; Anne Hartebrodt; Balázs Orbán; Sándor Fejér; Olga I. Zolotareva; Mohammad Bakhtiari; Béla Bihari; Marcus D. Bloice; Nina C. Donner; et al. (CoRR, 2021)

HyFed: A Hybrid Federated Framework for Privacy-preserving Machine Learning. - Reza Nasirigerdeh; Reihaneh Torkzadehmahani; Julian O. Matschinske; Jan Baumbach; Daniel Rueckert; Georgios Kaissis (CoRR, 2021)

Label Noise-Robust Learning using a Confidence-Based Sieving Strategy. - Reihaneh Torkzadehmahani; Reza Nasirigerdeh; Daniel Rueckert; Georgios Kaissis (Trans. Mach. Learn. Res., 2023)

Improved Localized Machine Unlearning Through the Lens of Memorization. - Reihaneh Torkzadehmahani; Reza Nasirigerdeh; Georgios Kaissis; Daniel Rueckert; Gintare Karolina Dziugaite; Eleni Triantafillou (CoRR, 2024)

Kernel Normalized Convolutional Networks. - Reza Nasirigerdeh; Reihaneh Torkzadehmahani; Daniel Rueckert; Georgios Kaissis (Trans. Mach. Learn. Res., 2024)