2 papers
math.OC2026
Natural Riemannian gradient for learning functional tensor networks
Nikolas Klug, Michael Ulbrich, André Uschmajew +1
We consider machine learning tasks with low-rank functional tree tensor networks (TTN) as the learning model. While in the case of least-squares regression, low-rank functional TTN…
math.OC2025
Riemannian Optimization on Tree Tensor Networks with Application in Machine Learning
Marius Willner, Marco Trenti, Dirk Lebiedz
Tree tensor networks (TTNs) are widely used in low-rank approximation and quantum many-body simulation. In this work, we present a formal analysis of the differential geometry unde…