9 papers
Universality of kernels on Riemannian symmetric spaces
Salem Said, Nathaël Da Costa, Franziskus Steinert +1
We investigate universality properties of continuous, positive-definite invariant kernels on Riemannian symmetric spaces, providing a unified harmonic-analytic characterization acr…
Routing on the Stiefel Manifold: When Does Adaptive Subspace Selection Help for Cross-Domain EEG Decoding?
Isabella Costa Maia, Pedro L. C. Rodrigues, Salem Said +1
Cross-domain EEG decoding remains challenging despite advances in Riemannian deep learning: covariance matrices from different subjects occupy systematically distinct regions of th…
Heat and Matérn Kernels on Matchings
Dmitry Eremeev, Salem Said, Viacheslav Borovitskiy
Applying kernel methods to matchings is challenging due to their discrete, non-Euclidean nature. In this paper, we develop a principled framework for constructing geometric kernels…
Curvature-based rejection sampling
Isabella Costa Maia, Marco Congedo, Pedro L. C. Rodrigues +1
The present work introduces curvature-based rejection sampling (CURS). This is a method for sampling from a general class of probability densities defined on Riemannian manifolds.…
Quasi-Synthetic Riemannian Data Generation for Writer-Independent Offline Signature Verification
Elias N. Zois, Moises Diaz, Salem Said +1
Offline handwritten signature verification remains a challenging task, particularly in writer-independent settings where models must generalize across unseen individuals. Recent de…
Gaussian integrals on symmetric spaces (the complex case and beyond)
Salem Said
The present work is concerned with Gaussian integrals on simply connected non-positively curved Riemannian symmetric spaces. It is motivated by the aim of explicitly finding the hi…