CNN Prediction of Future Disease Activity for Multiple Sclerosis Patients from Baseline MRI and Lesion Labels. - Nazanin Mohammadi Sepahvand; Tal Hassner; Douglas L. Arnold; Tal Arbel (BrainLes@MICCAI (1), 2018)

Improving Pathological Structure Segmentation via Transfer Learning Across Diseases. - Barleen Kaur; Paul Lemaître; Raghav Mehta; Nazanin Mohammadi Sepahvand; Doina Precup; Douglas L. Arnold; Tal Arbel (DART/MIL3ID@MICCAI, 2019)

CNN Detection of New and Enlarging Multiple Sclerosis Lesions from Longitudinal Mri Using Subtraction Images. - Nazanin Mohammadi Sepahvand; Douglas L. Arnold; Tal Arbel (ISBI, 2020)

HAD-Net: A Hierarchical Adversarial Knowledge Distillation Network for Improved Enhanced Tumour Segmentation Without Post-Contrast Images. - Saverio Vadacchino; Raghav Mehta; Nazanin Mohammadi Sepahvand; Brennan Nichyporuk; James J. Clark; Tal Arbel (MIDL, 2021)

Accounting for Variance in Machine Learning Benchmarks. - Xavier Bouthillier; Pierre Delaunay; Mirko Bronzi; Assya Trofimov; Brennan Nichyporuk; Justin Szeto; Nazanin Mohammadi Sepahvand; Edward Raff; Kanika Madan; Vikram Voleti; Samira Ebrahimi Kahou; Vincent Michalski; et al. (MLSys, 2021)

BD-KD: Balancing the Divergences for Online Knowledge Distillation. - Ibtihel Amara; Nazanin Mohammadi Sepahvand; Brett H. Meyer; Warren J. Gross; James J. Clark (CoRR, 2022)

Data Selection for Transfer Unlearning. - Nazanin Mohammadi Sepahvand; Vincent Dumoulin; Eleni Triantafillou; Gintare Karolina Dziugaite (CoRR, 2024)

Selective Unlearning via Representation Erasure Using Domain Adversarial Training. - Nazanin Mohammadi Sepahvand; Eleni Triantafillou; Hugo Larochelle; Doina Precup; James J. Clark; Daniel M. Roy 001; Gintare Karolina Dziugaite (ICLR, 2025)

Leveraging Per-Instance Privacy for Machine Unlearning. - Nazanin Mohammadi Sepahvand; Anvith Thudi; Berivan Isik; Ashmita Bhattacharyya; Nicolas Papernot; Eleni Triantafillou; Daniel M. Roy 001; Gintare Karolina Dziugaite (CoRR, 2025)