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In this paper we study global distance estimates and uniform local volume estimates in a large class of sub-Riemannian manifolds. Our main device is the generalized curvature dimension inequality introduced by the first and the third author…

Differential Geometry · Mathematics 2014-07-31 Fabrice Baudoin , Michel Bonnefont , Nicola Garofalo , Isidro H. Munive

We obtain an explicit determinantal formula for the multiplicity of any point on a classical Schubert variety.

Algebraic Geometry · Mathematics 2007-05-23 J. Rosenthal , A. Zelevinsky

Many variants of the Wasserstein distance have been introduced to reduce its original computational burden. In particular the Sliced-Wasserstein distance (SW), which leverages one-dimensional projections for which a closed-form solution of…

Machine Learning · Statistics 2023-01-31 Clément Bonet , Paul Berg , Nicolas Courty , François Septier , Lucas Drumetz , Minh-Tan Pham

Let $k$ be an algebraically closed field and ${\sf G}(2,k^4)$ the Grassmannian of 2-planes in $k^4$. We associate to each 6-dimensional subspace $R$ of the space of 4x4 matrices over $k$ a closed subscheme ${\bf X}_R \subseteq {\sf…

Rings and Algebras · Mathematics 2018-06-15 Alex Chirvasitu , S. Paul Smith , Michaela Vancliff

Combining the tools of geometric analysis with properties of Jordan angles and angle space distributions, we derive a spherical and a Euclidean Bernstein theorem for minimal submanifolds of arbitrary dimension and codimension, under the…

Differential Geometry · Mathematics 2014-05-26 J. Jost , Y. L. Xin , Ling Yang

Latent variable models are powerful tools for learning low-dimensional manifolds from high-dimensional data. However, when dealing with constrained data such as unit-norm vectors or symmetric positive-definite matrices, existing approaches…

Machine Learning · Computer Science 2025-03-10 Leonel Rozo , Miguel González-Duque , Noémie Jaquier , Søren Hauberg

In recent years, interest in extra dimensions has experienced a dramatic increase. A common practice has been to look for higher-dimensional generalizations of four-dimensional solutions to the Einstein equations. In this vein, we have…

General Relativity and Quantum Cosmology · Physics 2007-05-23 R. Steven Millward

Recent advances in computer vision and machine learning suggest that a wide range of problems can be addressed more appropriately by considering non-Euclidean geometry. In this paper we explore sparse dictionary learning over the space of…

Computer Vision and Pattern Recognition · Computer Science 2013-10-21 Mehrtash Harandi , Conrad Sanderson , Chunhua Shen , Brian C. Lovell

Restricted secant varieties of Grassmannians are constructed from sums of points corresponding to $k$-planes with the restriction that their intersection has a prescribed dimension. We study dimensions of restricted secant of Grassmannians…

Algebraic Geometry · Mathematics 2023-12-06 Dalton Bidleman , Luke Oeding

We introduce and explore a new concept of evasive subspace with respect to a collection of subspaces sharing a common dimension, most notably partial spreads. We show that this concept generalises known notions of subspace scatteredness and…

Combinatorics · Mathematics 2023-10-17 Anina Gruica , Alberto Ravagnani , John Sheekey , Ferdinando Zullo

Dimensionality reduction is a fundamental task that aims to simplify complex data by reducing its feature dimensionality while preserving essential patterns, with core applications in data analysis and visualisation. To preserve the…

Computer Vision and Pattern Recognition · Computer Science 2025-04-01 Thomas Dagès , Simon Weber , Ya-Wei Eileen Lin , Ronen Talmon , Daniel Cremers , Michael Lindenbaum , Alfred M. Bruckstein , Ron Kimmel

We propose a covariant and geometric framework to introduce space distances as they are used by astronomers. In particular, we extend the definition of space distances from the one used between events to non-test-bodies with horizons and…

General Relativity and Quantum Cosmology · Physics 2022-01-11 Salvatore Capozziello , Alice Chiappini , Lorenzo Fatibene , Andrea Orizzonte

We produce a family of reductions for Schubert intersection problems whose applicability is checked by calculating a linear combination of the dimensions involved. These reductions do not alter the Littlewood-Richardson coefficient, and…

Combinatorics · Mathematics 2009-09-07 H. Bercovici , W. S. Li , D. Timotin

A general geometrical scheme is presented for the construction of novel classical gravity theories whose solutions obey two-sided bounds on the sectional curvatures along certain subvarieties of the Grassmannian of two-planes. The…

High Energy Physics - Theory · Physics 2007-05-23 Frederic P. Schuller , Mattias N. R. Wohlfarth

The Gromov-Hausdorff distance measures the similarity between two metric spaces by isometrically embedding them into an ambient metric space. We introduce an analogue of this distance for metric spaces endowed with directed structures. The…

The Gromov-Wasserstein (GW) distance is frequently used in machine learning to compare distributions across distinct metric spaces. Despite its utility, it remains computationally intensive, especially for large-scale problems. Recently, a…

Machine Learning · Statistics 2024-10-01 Antoine Salmona , Julie Delon , Agnès Desolneux

Making sense of Wasserstein distances between discrete measures in high-dimensional settings remains a challenge. Recent work has advocated a two-step approach to improve robustness and facilitate the computation of optimal transport, using…

Machine Learning · Computer Science 2019-09-04 François-Pierre Paty , Marco Cuturi

Formulations of some Grassmann-valued systems of ordinary differential equations invariant under (infinitesimal) supersymmetry transformations, including $N$-superspace extended types, are reviewed and discussed, with use of superfields.…

Mathematical Physics · Physics 2019-03-29 M. Legare

We give a new asymptotic upper bound on the size of a code in the Grassmannian space. The bound is better than the upper bounds known previously in the entire range of distances except very large values.

Information Theory · Computer Science 2019-05-14 Alexander Barg , Dmitry Nogin

Due to the growing interest in embeddings of space-time in higher-dimensional spaces we consider a specific type of embedding. After proving an inequality between intrinsically defined curvature invariants and the squared mean curvature, we…

General Relativity and Quantum Cosmology · Physics 2009-11-10 Stefan Haesen , Leopold Verstraelen