output
20072024
most citedDeriving reproducible biomarkers from multi-site resting-state data: An Autism-based example

742 citations

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6 papers · 1 filter

cs.CV20242 cited

ADAPT: Multimodal Learning for Detecting Physiological Changes under Missing Modalities

Julie Mordacq, Leo Milecki, Maria Vakalopoulou +2

Multimodality has recently gained attention in the medical domain, where imaging or video modalities may be integrated with biomedical signals or health records. Yet, two challenge…

cs.CV2024

PoNQ: a Neural QEM-based Mesh Representation

Nissim Maruani, Maks Ovsjanikov, Pierre Alliez +1

Although polygon meshes have been a standard representation in geometry processing, their irregular and combinatorial nature hinders their suitability for learning-based applicatio…

cs.CV20231 cited

Diverse Diffusion: Enhancing Image Diversity in Text-to-Image Generation

Mariia Zameshina, Olivier Teytaud, Laurent Najman

Latent diffusion models excel at producing high-quality images from text. Yet, concerns appear about the lack of diversity in the generated imagery. To tackle this, we introduce Di…

cs.CV202214 cited

Learning Multi-resolution Functional Maps with Spectral Attention for Robust Shape Matching

Lei Li, Nicolas Donati, Maks Ovsjanikov

In this work, we present a novel non-rigid shape matching framework based on multi-resolution functional maps with spectral attention. Existing functional map learning methods all…

cs.CV2011148 cited

A supervised clustering approach for fMRI-based inference of brain states

Vincent Michel, Alexandre Gramfort, Gaël Varoquaux +3

We propose a method that combines signals from many brain regions observed in functional Magnetic Resonance Imaging (fMRI) to predict the subject's behavior during a scanning sessi…

cs.CV2011140 cited

Total variation regularization for fMRI-based prediction of behaviour

Vincent Michel, Alexandre Gramfort, Gaël Varoquaux +2

While medical imaging typically provides massive amounts of data, the extraction of relevant information for predictive diagnosis remains a difficult challenge. Functional MRI (fMR…