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Riemannian geometry is a mathematical field which has been the cornerstone of revolutionary scientific discoveries such as the theory of general relativity. Despite early uses in robot design and recent applications for exploiting data with…

Robotics · Computer Science 2022-10-03 Noémie Jaquier , Tamim Asfour

The geometric approach to optimal transport and information theory has triggered the interpretation of probability densities as an infinite-dimensional Riemannian manifold. The most studied Riemannian structures are Otto's metric, yielding…

Analysis of PDEs · Mathematics 2018-07-20 Martin Bauer , Sarang Joshi , Klas Modin

Constant rescaling of a Riemannian metric appears in many computational settings, often through a global scale parameter that is introduced either explicitly or implicitly. Although this operation is elementary, its consequences are not…

Machine Learning · Computer Science 2026-01-29 Kisung You

We consider the results of combining two approaches developed for the design of Riemannian metrics on curves and surfaces, namely parametrization-invariant metrics of the Sobolev type on spaces of immersions, and metrics derived through…

Differential Geometry · Mathematics 2018-04-24 Laurent Younes

What is the optimal way to deform a projective hypersurface into another one? In this paper we will answer this question adopting the point of view of measure theory, introducing the optimal transport problem between complex algebraic…

Differential Geometry · Mathematics 2023-07-18 Paolo Antonini , Fabio Cavalletti , Antonio Lerario

Learning the covariance matrices of spatially-correlated wireless channels, in millimeter-wave (mmWave) vehicular communication, can be utilized in designing environmen-taware beamforming codebooks. Such channel covariance matrices can be…

Signal Processing · Electrical Eng. & Systems 2021-07-05 Imtiaz Nasim , Ahmed S. Ibrahim

An information-geometric approach to sensor management is introduced that is based on following geodesic curves in a manifold of possible sensor configurations. This perspective arises by observing that, given a parameter estimation problem…

Applications · Statistics 2016-11-15 Bill Moran , Stephen D. Howard , Douglas Cochran

The analysis of manifold-valued data requires efficient tools from Riemannian geometry to cope with the computational complexity at stake. This complexity arises from the always-increasing dimension of the data, and the absence of…

Computer Vision and Pattern Recognition · Computer Science 2017-11-27 Maxime Louis , Alexandre Bône , Benjamin Charlier , Stanley Durrleman

If M is a smooth compact connected Riemannian manifold, let P(M) denote the Wasserstein space of probability measures on M. We describe a geometric construction of parallel transport of some tangent cones along geodesics in P(M). We show…

Differential Geometry · Mathematics 2017-01-10 John Lott

In this paper, we address several interconnected problems in the theory of harmonic maps between Riemannian manifolds. First, we present necessary background and establish one of the main results of the paper: a criterion characterizing…

Differential Geometry · Mathematics 2025-07-14 Sergey Stepanov , Irina Tsyganok

We explore the conceptual usefulness of Riemannian geometric tools induced by the statistical concept of distinguishability in quantifying the effect of a depolarizing channel on quantum states. Specifically, we compare the geometries of…

Mathematical Physics · Physics 2012-05-01 Carlo Cafaro , Stefano Mancini

Comparing images to recommend items from an image-inventory is a subject of continued interest. Added with the scalability of deep-learning architectures the once `manual' job of hand-crafting features have been largely alleviated, and…

Information Retrieval · Computer Science 2017-11-15 Y Qian , E Vazquez , B Sengupta

The paper is a study of geodesic in two-dimensional pseudo-Riemannian metrics. Firstly, the local properties of geodesics in a neighborhood of generic parabolic points are investigated. The equation of the geodesic flow has singularities at…

Differential Geometry · Mathematics 2016-11-22 Alexey Remizov

We explore the use of tools from Riemannian geometry for the analysis of symmetric positive definite matrices (SPD). An SPD matrix is a versatile data representation that is commonly used in chemical engineering (e.g.,…

Applications · Statistics 2022-03-24 Alexander Smith , Benjamin Laubach , Ivan Castillo , Victor M. Zavala

The geodesic orbit property is useful and interesting in itself, and it plays a key role in Riemannian geometry. It implies homogeneity and has important classes of Riemannian manifolds as special cases. Those classes include weakly…

Differential Geometry · Mathematics 2023-07-18 Zhiqi Chen , Yuri Nikolayevsky , Joseph A. Wolf , Shaoxiang Zhang

Geodesics escape is widely used to study the scattering of hyperbolic equations. However, there are few progresses except in a simply connected complete Riemannian manifold with nonpositive curvature. We propose a kind of complete…

Analysis of PDEs · Mathematics 2018-12-03 Zhen-Hu Ning , Fengyan Yang , Xiaopeng Zhao

This paper sheds light on the essential characteristics of geodesics, which frequently occur in considerations from motion in Euclidean space. Focus is mainly on a method of obtaining them from the calculus of variations, and an explicit…

General Mathematics · Mathematics 2017-03-21 Uchechukwu Michael Opara

These notes on Riemannian geometry use the bases bundle and frame bundle, as in Geometry of Manifolds, to express the geometric structures. It has more problems and omits the background material. It starts with the definition of Riemannian…

Differential Geometry · Mathematics 2013-07-30 Richard L. Bishop

We propose a unifying framework for generalising the Wasserstein-1 metric to a discrepancy measure between nonnegative measures of different mass. This generalization inherits the convexity and computational efficiency from the…

Optimization and Control · Mathematics 2018-03-13 Bernhard Schmitzer , Benedikt Wirth

For the purposes of abstract theory of signal propagation, a signal is a submanifold of a Riemannian manifold. We obtain energy inequalities, or upper bounds, lower bounds on energy in a number of specific cases, including parameter spaces…

Information Theory · Computer Science 2025-04-15 Tatyana Barron , Spencer Kelly , Colin Poulton