5 citations · 11 across the 16 of their papers we have counts for
9 papers · 1 filter
Decoding Naturalistic Speech from fMRI with Temporal Modeling and Multimodal Alignment
Corentin Caris, Louis Jalouzot, Nona Rajabi +9
Reconstructing what a person perceives from their brain activity is a stringent test of whether neural recordings carry meaningful information. Naturalistic speech offers a rich te…
Cephalonauts One: A deep fMRI dataset for decoding naturalistic speech in the human brain
Antoine Collas, Louis Jalouzot, Géraud Ilinca +11
Cephalonauts One is a whole-brain 3 Tesla (3T) functional magnetic resonance imaging (fMRI) dataset recorded while subjects listened to audio podcasts. Three healthy subjects under…
Riemannian Flow Matching for Brain Connectivity Matrices via Pullback Geometry
Antoine Collas, Ce Ju, Nicolas Salvy +1
Generating realistic brain connectivity matrices is key to analyzing population heterogeneity in brain organization, understanding disease, and augmenting data in challenging class…
An Automated Pipeline for Few-Shot Bird Call Classification: A Case Study with the Tooth-Billed Pigeon
Abhishek Jana, Moeumu Uili, James Atherton +3
This paper presents a largely automated one-shot bird call classification pipeline, incorporating targeted manual quality control steps, designed for rare species absent from large…
PSDNorm: Test-Time Temporal Normalization for Deep Learning in Sleep Staging
Théo Gnassounou, Antoine Collas, Rémi Flamary +1
Distribution shift poses a significant challenge in machine learning, particularly in biomedical applications using data collected across different subjects, institutions, and reco…
Multi-Source and Test-Time Domain Adaptation on Multivariate Signals using Spatio-Temporal Monge Alignment
Théo Gnassounou, Antoine Collas, Rémi Flamary +2
Machine learning applications on signals such as computer vision or biomedical data often face significant challenges due to the variability that exists across hardware devices or…
SKADA-Bench: Benchmarking Unsupervised Domain Adaptation Methods with Realistic Validation On Diverse Modalities
Yanis Lalou, Théo Gnassounou, Antoine Collas +6
Unsupervised Domain Adaptation (DA) consists of adapting a model trained on a labeled source domain to perform well on an unlabeled target domain with some data distribution shift.…
Parametric information geometry with the package Geomstats
Alice Le Brigant, Jules Deschamps, Antoine Collas +1
We introduce the information geometry module of the Python package Geomstats. The module first implements Fisher-Rao Riemannian manifolds of widely used parametric families of prob…
Riemannian optimization for non-centered mixture of scaled Gaussian distributions
Antoine Collas, Arnaud Breloy, Chengfang Ren +2
This paper studies the statistical model of the non-centered mixture of scaled Gaussian distributions (NC-MSG). Using the Fisher-Rao information geometry associated to this distrib…