6 papers
Benchmarking External Generalization of SPD Matrix Learning for Resting-State fMRI Connectome Prediction
Ce Ju, Antoine Collas, Florent Bouchard +1
Resting-state functional magnetic resonance imaging (rs-fMRI) functional connectivity (FC) matrices are widely used for individual-level prediction, but strong performance within o…
Sheaf Neural Networks on SPD Manifolds: Second-Order Geometric Representation Learning
Yuhan Peng, Junwen Dong, Yuzhi Zeng +6
Graph neural networks face two fundamental challenges rooted in the linear structure of Euclidean vector spaces: (1) Current architectures represent geometry through vectors (direc…
SPD Learn: A Geometric Deep Learning Python Library for Neural Decoding Through Trivialization
Bruno Aristimunha, Ce Ju, Antoine Collas +5
Implementations of symmetric positive definite (SPD) matrix-based neural networks for neural decoding remain fragmented across research codebases and Python packages. Existing impl…
Cross-Session Decoding of Neural Spiking Data via Task-Conditioned Latent Alignment
Canyang Zhao, Bolin Peng, J. Patrick Mayo +2
Training a high-performing neural decoder can be difficult when only limited data are available from a recording session. To address this challenge, we propose a Task-Conditioned L…
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…