4 papers
FedSPDnet: Geometry-Aware Federated Deep Learning with SPDnet
Thibault Pautrel, Florent Bouchard, Ammar Mian +1
We introduce two federated learning frameworks for the classical SPDnet model operating on symmetric positive definite (SPD) matrices with Stiefel-constrained parameters. Unlike st…
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…
Generalized Nonnegative Structured Kruskal Tensor Regression
Xinjue Wang, Esa Ollila, Sergiy A. Vorobyov +1
This paper introduces Generalized Nonnegative Structured Kruskal Tensor Regression (NS-KTR), a novel tensor regression framework that enhances interpretability and performance thro…
Classification of Buried Objects from Ground Penetrating Radar Images by using Second Order Deep Learning Models
Douba Jafuno, Ammar Mian, Guillaume Ginolhac +1
In this paper, a new classification model based on covariance matrices is built in order to classify buried objects. The inputs of the proposed models are the hyperbola thumbnails…