Geometric Feature Learning for Functional Data Valued on the Symmetric Positive Definite Manifold

arXiv:2609.30487v1 Announce Type: cross Abstract: We here develop a functional neural network, termed MatFAE, for learning trajectories on the Riemannian manifold of symmetric positive definite (SPD) matrices. MatFAE features intrinsic layers that map manifold-valued functions to Euclidean vector-v…

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1. 2026-09-28 04:00 · arXiv stat.ML
   Geometric Feature Learning for Functional Data Valued on the Symmetric Positive Definite Manifold