96 citations · 96 across the 2 of their papers we have counts for
3 papers
Geomstats: A Python Package for Riemannian Geometry in Machine Learning
Nina Miolane, Alice Le Brigant, Johan Mathe +16
We introduce Geomstats, an open-source Python toolbox for computations and statistics on nonlinear manifolds, such as hyperbolic spaces, spaces of symmetric positive definite matri…
From Node Embedding To Community Embedding : A Hyperbolic Approach
Thomas Gerald, Hadi Zaatiti, Hatem Hajri +2
Detecting communities on graphs has received significant interest in recent literature. Current state-of-the-art community embedding approach called \textit{ComE} tackles this prob…
Binary Stochastic Representations for Large Multi-class Classification
Thomas Gerald, Aurélia Léon, Nicolas Baskiotis +1
Classification with a large number of classes is a key problem in machine learning and corresponds to many real-world applications like tagging of images or textual documents in so…