A Penalized Subspace Strategy for Solving Large-Scale Constrained Optimization Problems. - Ségolène Martin; Emilie Chouzenoux; Jean-Christophe Pesquet (EUSIPCO, 2021)

A Non-Convex Proximal Approach for Centroid-Based Classification. - Mewe-Hezoudah Kahanam; Laurent Le Brusquet; Ségolène Martin; Jean-Christophe Pesquet (ICASSP, 2022)

Towards Practical Few-shot Query Sets: Transductive Minimum Description Length Inference. - Ségolène Martin; Malik Boudiaf; Emilie Chouzenoux; Jean-Christophe Pesquet; Ismail Ben Ayed (NeurIPS, 2022)

On a fixed-point continuation method for a convex optimization problem. - Jean-Baptiste Fest; Tommi Heikkilä; Ignace Loris; Ségolène Martin; Luca Ratti; Simone Rebegoldi; Gesa Sarnighausen (CoRR, 2022)

A Local MM Subspace Method for Solving Constrained Variational Problems in Image Recovery. - Emilie Chouzenoux; Ségolène Martin; Jean-Christophe Pesquet (J. Math. Imaging Vis., 2023)

Transductive Zero-Shot and Few-Shot CLIP. - Ségolène Martin; Yunshi Huang; Fereshteh Shakeri; Jean-Christophe Pesquet; Ismail Ben Ayed (CVPR, 2024)

A Transductive Few-Shot Learning Approach for Classification of Digital Histopathological Slides from Liver Cancer. - Aymen Sadraoui; Ségolène Martin; Eliott Barbot; Astrid Laurent-Bellue; Jean-Christophe Pesquet; Catherine Guettier; Ismail Ben Ayed (ISBI, 2024)

Variational methods for large-scale data problems in imaging. (Méthodes variationnelles pour les problèmes de données à grande échelle en imagerie). - Ségolène Martin (2024)

PnP-Flow: Plug-and-Play Image Restoration with Flow Matching. - Ségolène Tiffany Martin; Anne Gagneux; Paul Hagemann; Gabriele Steidl (ICLR, 2025)

Deep Generative Clustering with VAEs and Expectation-Maximization. - Michael Adipoetra; Ségolène Martin (SSVM (1), 2025)

Variable Bregman Majorization-Minimization Algorithm and its Application to Dirichlet Maximum Likelihood Estimation. - Ségolène Martin; Jean-Christophe Pesquet; Gabriele Steidl; Ismail Ben Ayed (CoRR, 2025)

Learning Brenier Potentials with Convex Generative Adversarial Neural Networks. - Claudia Drygala; Hanno Gottschalk; Thomas Kruse; Ségolène Martin; Annika Mütze (CoRR, 2025)