Benoit Dufumier

What to align in multimodal contrastive learning?

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

Anatomical Foundation Models for Brain MRIs

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

Contrastive Learning with Continuous Proxy Meta-Data for 3D MRI Classification

Traditional supervised learning with deep neural networks requires a tremendous amount of labelled data to converge to a good solution. For 3D medical images, it is often impractical to build a...

Conditional Alignment and Uniformity for Contrastive Learning with Continuous Proxy Labels

Contrastive Learning has shown impressive results on natural and medical images, without requiring annotated data. However, a particularity of medical images is the availability of meta-data (such...

UCSL : A Machine Learning Expectation-Maximization framework for Unsupervised Clustering driven by Supervised Learning

Subtype Discovery consists in finding interpretable and consistent sub-parts of a dataset, which are also relevant to a certain supervised task. From a mathematical point of view, this can be...

How and Why Does Deep Ensemble Coupled with Transfer Learning Increase Performance in Bipolar Disorder and Schizophrenia Classification?

Contrastive Learning for Regression in Multi-Site Brain Age Prediction

Supervised Diagnosis Prediction from Cortical Sulci: Toward the Discovery of Neurodevelopmental Biomarkers in Mental Disorders

Unbiased Supervised Contrastive Learning

What to align in multimodal contrastive learning?

SepVAE: a contrastive VAE to separate pathological patterns from healthy ones

UCSL : A Machine Learning Expectation-Maximization Framework for Unsupervised Clustering Driven by Supervised Learning

Detection of Abnormal Folding Patterns with Unsupervised Deep Generative Models

Contrastive Learning with Continuous Proxy Meta-data for 3D MRI Classification

Unsupervised Representation Learning of Cingulate Cortical Folding Patterns

Does Connectome Harmonic Analysis Pass the Spin Test?

MixUp Brain-Cortical Augmentations in Self-supervised Learning

Integrating Prior Knowledge in Contrastive Learning with Kernel