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We consider a class of piecewise hyperbolic maps from the unit square to itself preserving a contracting foliation and inducing a piecewise expanding quotient map, with infinite derivative (like the first return maps of Lorenz like flows).…

Dynamical Systems · Mathematics 2017-10-05 Stefano Galatolo , Isaia Nisoli

On a smooth connected manifold, we consider all possible locally elliptic and locally bounded measurable coefficient Riemannian metrics called rough Riemannian metrics. We equip this set with an extended metric which is connected if and…

Differential Geometry · Mathematics 2025-07-15 Lashi Bandara , Anisa Hassan

We study the discretization of generalized Wasserstein distances with nonlinear mobilities on the real line via suitable discrete metrics on the cone of N ordered particles, a setting which naturally appears in the framework of…

Analysis of PDEs · Mathematics 2022-09-01 Simone Di Marino , Lorenzo Portinale , Emanuela Radici

We study $\infty$-modulus on general metric spaces and establish its relation to shortest lengths of paths. This connection was already known for modulus on graphs, but the formulation in metric measure spaces requires more attention to…

Metric Geometry · Mathematics 2021-02-09 Nathan Albin , Jared Hoppis , Pietro Poggi-Corradini , Nageswari Shanmugalingam

The Quasi Manhattan Wasserstein Distance (QMWD) is a metric designed to quantify the dissimilarity between two matrices by combining elements of the Wasserstein Distance with specific transformations. It offers improved time and space…

Machine Learning · Computer Science 2023-10-20 Evan Unit Lim

The space of Gaussian measures on a Euclidean space is geodesically convex in the $L^2$-Wasserstein space. This space is a finite dimensional manifold since Gaussian measures are parameterized by means and covariance matrices. By…

Differential Geometry · Mathematics 2009-02-11 Asuka Takatsu

Persistence diagrams (PD)s play a central role in topological data analysis, and are used in an ever increasing variety of applications. The comparison of PD data requires computing comparison metrics among large sets of PDs, with metrics…

Computational Geometry · Computer Science 2024-02-23 Rolando Kindelan Nuñez , Mircea Petrache , Mauricio Cerda , Nancy Hitschfeld

In physics, two systems that radically differ at short scales can exhibit strikingly similar macroscopic behaviour: they are part of the same long-distance universality class. Here we apply this viewpoint to geometry and initiate a program…

High Energy Physics - Theory · Physics 2023-11-22 Adam R. Brown , Michael H. Freedman , Henry W. Lin , Leonard Susskind

Plausibility is a formalization of exact tests for parametric models and generalizes procedures such as Fisher's exact test. The resulting tests are based on cumulative probabilities of the probability density function and evaluate…

Statistics Theory · Mathematics 2021-09-13 Stefan Böhringer , Dietmar Lohmann

In this paper we propose an algorithm for aligning three-dimensional objects when represented as density maps, motivated by applications in cryogenic electron microscopy. The algorithm is based on minimizing the 1-Wasserstein distance…

Image and Video Processing · Electrical Eng. & Systems 2024-03-13 Amit Singer , Ruiyi Yang

We introduce a novel approach to Maximum A Posteriori inference based on discrete graphical models. By utilizing local Wasserstein distances for coupling assignment measures across edges of the underlying graph, a given discrete objective…

Machine Learning · Computer Science 2018-05-29 Ruben Hühnerbein , Fabrizio Savarino , Freddie Åström , Christoph Schnörr

In the study of dynamical and physical systems, the input parameters are often uncertain or randomly distributed according to a measure $\varrho$. The system's response $f$ pushes forward $\varrho$ to a new measure $f\circ \varrho$ which we…

Classical Analysis and ODEs · Mathematics 2019-11-15 Amir Sagiv

The inevitable noise in real measurements motivates the problem to continuously quantify the similarity between rigid objects such as periodic time series and proteins given by ordered points and considered up to isometry maintaining…

Computational Geometry · Computer Science 2022-07-19 Vitaliy Kurlin

Motivated by the 2D class averaging problem in single-particle cryo-electron microscopy (cryo-EM), we present a k-means algorithm based on a rotationally-invariant Wasserstein metric for images. Unlike existing methods that are based on…

Computer Vision and Pattern Recognition · Computer Science 2021-05-31 Rohan Rao , Amit Moscovich , Amit Singer

Generalized Wasserstein distances allow to quantitatively compare two continuous or atomic mass distributions with equal or different total mass. In this paper, we propose four numerical methods for the approximation of three different…

Analysis of PDEs · Mathematics 2025-10-21 Maya Briani , Emiliano Cristiani , Giovanni Franzina , Francesca L. Ignoto

Motivated by the Bures distance, we introduce a new family of distances, \emph{relative translation invariant Wasserstein distances}, denoted by $RW_p$, as an extension of the classical Wasserstein distances $W_p$ for $p \in [1, +\infty)$.…

Machine Learning · Computer Science 2026-05-26 Binshuai Wang , Qiwei Di , Ming Yin , Mengdi Wang , Quanquan Gu , Peng Wei

In topological data science, categories with a flow have become ubiquitous, including as special cases examples like persistence modules and sheaves. With the flow comes an interleaving distance, which has proven useful for applications. We…

Category Theory · Mathematics 2019-01-16 Joshua Cruz

A weight module of a basic Lie superalgebra is called finite if all of its weight spaces are finite dimensional, and it is called bounded if there is a uniform bound on the dimension of a weight space. The minimum bound is called the degree…

Representation Theory · Mathematics 2013-11-12 Crystal Hoyt

Generating point clouds, e.g., molecular structures, in arbitrary rotations, translations, and enumerations remains a challenging task. Meanwhile, neural networks utilizing symmetry invariant layers have been shown to be able to optimize…

Machine Learning · Computer Science 2019-11-18 Moritz Hoffmann , Frank Noé

In this article we initiate a systematic study of irreducible weight modules over direct limits of reductive Lie algebras, and in particular over the simple Lie algebras $A(\infty)$, $B(\infty)$, $C(\infty)$ and $D(\infty)$. Our main tool…

Representation Theory · Mathematics 2007-05-23 Ivan Dimitrov , Ivan Penkov