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We provide a geometric interpretation to Bayesian inference that allows us to introduce a natural measure of the level of agreement between priors, likelihoods, and posteriors. The starting point for the construction of our geometry is the…

Methodology · Statistics 2018-05-24 Miguel de Carvalho , Garritt L. Page , Bradley J. Barney

Given a smooth Riemannian manifold $(M,g)$, compact and without boundary, we analyze the dynamical optimal mass transport problem where the cost is given by the sum of the kinetic energy and the relative entropy with respect to a reference…

Analysis of PDEs · Mathematics 2024-01-05 Gabriele Bocchi , Alessio Porretta

We develop an intrinsic geometric approach to calculus of variations on Wasserstein space. We show that the flows associated to the Schroedinger bridge with general prior, to Optimal Mass Transport and to the Madelung fluid can all be…

Mathematical Physics · Physics 2017-12-07 Giovanni Conforti , Michele Pavon

A manifold is a space that locally looks like the smooth space $\mathbf{R}^{n}$. It is usually also assumed that the underlying topological space of a manifold is hausdorff. However, there are natural examples of manifolds for which the…

General Topology · Mathematics 2023-10-17 John Dougherty

Let $M$, $N$ be finite-dimensional manifolds with $M$ compact. This paper looks at the Riemnannian geometry on the space $C^\infty(M,N)$ of smooth maps equipped with the $L^2$-Riemannian metric. This metric was used by Ebin and Marsden in…

Differential Geometry · Mathematics 2018-04-03 Martins Bruveris

We present a constructive approach to surface comparison realizable by a polynomial-time algorithm. We determine the "similarity" of two given surfaces by solving a mass-transportation problem between their conformal densities. This mass…

Differential Geometry · Mathematics 2011-10-25 Yaron Lipman , Ingrid Daubechies

The space of all non degenerate bilinear structures on a manifold $M$ carries a one parameter family of pseudo Riemannian metrics. We determine the geodesic equation, covariant derivative, curvature, and we solve the geodesic equation…

Differential Geometry · Mathematics 2016-09-06 Olga Gil-Medrano , Peter W. Michor , Martin Neuwirther

Given a smooth free action of a compact connected Lie group $G$ on a smooth compact manifold $M$, we show that the space of $G$-invariant Riemannian metrics on $M$ whose automorphism group is precisely $G$ is open dense in the space of all…

Differential Geometry · Mathematics 2021-03-26 Alexandru Chirvasitu

Optimal transport (OT) and the related Wasserstein metric (W) are powerful and ubiquitous tools for comparing distributions. However, computing pairwise Wasserstein distances rapidly becomes intractable as cohort size grows. An attractive…

Machine Learning · Computer Science 2024-06-05 Doron Haviv , Russell Zhang Kunes , Thomas Dougherty , Cassandra Burdziak , Tal Nawy , Anna Gilbert , Dana Pe'er

We show Riemannian geometry could be studied by identifying the tangent bundle of a Riemannian manifold $\mathcal{M}$ with a subbundle of the trivial bundle $\mathcal{M} \times \mathcal{E}$, obtained by embedding $\mathcal{M}$…

Differential Geometry · Mathematics 2021-05-05 Du Nguyen

The Wasserstein space of probability measures is known for its intricate Riemannian structure, which underpins the Wasserstein geometry and enables gradient flow algorithms. However, the Wasserstein geometry may not be suitable for certain…

Analysis of PDEs · Mathematics 2025-05-23 Zhengxin Zhang , Ziv Goldfeld , Kristjan Greenewald , Youssef Mroueh , Bharath K. Sriperumbudur

Wasserstein 1 optimal transport maps provide a natural correspondence between points from two probability distributions, $\mu$ and $\nu$, which is useful in many applications. Available algorithms for computing these maps do not appear to…

Optimization and Control · Mathematics 2022-11-03 Tristan Milne , Étienne Bilocq , Adrian Nachman

Random probabilities are a key component to many nonparametric methods in Statistics and Machine Learning. To quantify comparisons between different laws of random probabilities several works are starting to use the elegant Wasserstein over…

Statistics Theory · Mathematics 2024-05-27 Marta Catalano , Hugo Lavenant

This study aims to better understand the functional geometry of the motor cortex, starting from different sources of experimental evidence. Recent studies have proved that cells of the primary motor cortex (M1) are sensitive to short hand…

Neurons and Cognition · Quantitative Biology 2026-03-24 Jawad Ali , Giovanna Citti , Alessandro Sarti

Optimal Transport (OT) metrics allow for defining discrepancies between two probability measures. Wasserstein distance is for longer the celebrated OT-distance frequently-used in the literature, which seeks probability distributions to be…

Machine Learning · Computer Science 2021-10-14 Mokhtar Z. Alaya , Gilles Gasso , Maxime Berar , Alain Rakotomamonjy

We study metric projections onto cones in the Wasserstein space of probability measures, defined by stochastic orders. Dualities for backward and forward projections are established under general conditions. Dual optimal solutions and their…

Probability · Mathematics 2021-10-12 Young-Heon Kim , Yuan Long Ruan

We study the stability of entropically regularized optimal transport with respect to the marginals. Lipschitz continuity of the value and H\"older continuity of the optimal coupling in $p$-Wasserstein distance are obtained under general…

Optimization and Control · Mathematics 2022-07-06 Stephan Eckstein , Marcel Nutz

In this paper, we study isometries of $p$-Wasserstein spaces. In our first result, for every complete and separable metric space $X$ and for every $p\geq1$, we construct a metric space $Y$ such that $X$ embeds isometrically into $Y$, and…

Metric Geometry · Mathematics 2025-10-20 Zoltán M. Balogh , Eric Ströher , Tamás Titkos , Dániel Virosztek

We deal with irregular curves contained in smooth, closed, and compact surfaces. For curves with finite total intrinsic curvature, a weak notion of parallel transport of tangent vector fields is well-defined in the Sobolev setting. Also,…

Differential Geometry · Mathematics 2021-05-17 Domenico Mucci , Alberto Saracco

We investigate here the optimal transportation problem on configuration space for the quadratic cost. It is shown that, as usual, provided that the corresponding Wasserstein is finite, there exists one unique optimal measure and that this…

Probability · Mathematics 2007-05-23 L. Decreusefond