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MiS Preprint

Learning Paths from Signature Tensors

Max Pfeffer, Anna Seigal and Bernd Sturmfels


Matrix congruence extends naturally to the setting of tensors. We apply methods from tensor decomposition, algebraic geometry and numerical optimization to this group action. Given a tensor in the orbit of another tensor, we compute a matrix which transforms one to the other. Our primary application is an inverse problem from stochastic analysis: the recovery of paths from their signature tensors of order three. We establish identifiability results and recovery algorithms for piecewise linear paths, polynomial paths, and generic dictionaries. A detailed analysis of the relevant condition numbers is presented. We also compute the shortest path with a given signature tensor.

Sep 10, 2018
Sep 10, 2018

Related publications

2019 Repository Open Access
Max Pfeffer, Anna Seigal and Bernd Sturmfels

Learning paths from signature tensors

In: SIAM journal on matrix analysis and applications, 40 (2019) 2, pp. 394-416