collaborators

6 papers

cs.LG2026

Automatic Discovery of Disease Subgroups by Contrasting with Healthy Controls

Robin Louiset, Edouard Duchesnay, Benoit Dufumier +2

In biomedical Subgroup Discovery, practitioners are interested in discovering interpretable and homogeneous subgroups within a group of patients. In this paper, assuming that healt…

cs.LG2026

A Unified Geometric Framework for Weighted Contrastive Learning

Raphael Vock, Edouard Duchesnay, Benoit Dufumier

Contrastive learning (CL) aims to preserve relational structure between samples by learning representations that reflect a similarity graph. Yet, the geometry of the resulting embe…

cs.AI2026

How and why does deep ensemble coupled with transfer learning increase performance in bipolar disorder and schizophrenia classification?

Sara Petiton, Antoine Grigis, Benoit Dufumier +1

Transfer learning (TL) and deep ensemble learning (DE) have recently been shown to outperform simple machine learning in classifying psychiatric disorders. However, there is still…

eess.IV2025

Robust brain age estimation from structural MRI with contrastive learning

Carlo Alberto Barbano, Benoit Dufumier, Edouard Duchesnay +2

Estimating brain age from structural MRI has emerged as a powerful tool for characterizing normative and pathological aging. In this work, we explore contrastive learning as a scal…

eess.IV2025

Anatomical Foundation Models for Brain MRIs

Carlo Alberto Barbano, Matteo Brunello, Benoit Dufumier +1

Deep Learning (DL) in neuroimaging has become increasingly relevant for detecting neurological conditions and neurodegenerative disorders. One of the most predominant biomarkers in…

cs.LG2025

What to align in multimodal contrastive learning?

Benoit Dufumier, Javiera Castillo-Navarro, Devis Tuia +1

Humans perceive the world through multisensory integration, blending the information of different modalities to adapt their behavior. Contrastive learning offers an appealing solut…