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This paper introduces Wasserstein variational inference, a new form of approximate Bayesian inference based on optimal transport theory. Wasserstein variational inference uses a new family of divergences that includes both f-divergences and…

We calculate the electronic transport properties of a system which is irradiated by a homogeneous microwave field. Within a Boltzmann equation approach, a general expression for the conductivity tensor is derived and evaluated for a quasi…

Condensed Matter · Physics 2009-10-28 Tobias Brandes

Designing experiments that systematically gather data from complex physical systems is central to accelerating scientific discovery. While Bayesian experimental design (BED) provides a principled, information-based framework that integrates…

Machine Learning · Computer Science 2026-01-26 Huchen Yang , Xinghao Dong , Jin-Long Wu

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 the conductivity of two-dimensional graphene-type materials with tilted cones as well as their three-dimensional Weyl counterparts and show that a covariant quantum Boltzmann equation is capable of providing an accurate description…

Mesoscale and Nanoscale Physics · Physics 2019-09-04 Saber Rostamzadeh , İnanç Adagideli , M. O. Goerbig

We formulate and solve a regression problem with time-stamped distributional data. Distributions are considered as points in the Wasserstein space of probability measures, metrized by the 2-Wasserstein metric, and may represent images,…

Systems and Control · Electrical Eng. & Systems 2021-06-30 Amirhossein Karimi , Tryphon T. Georgiou

The Wasserstein probability metric has received much attention from the machine learning community. Unlike the Kullback-Leibler divergence, which strictly measures change in probability, the Wasserstein metric reflects the underlying…

Machine Learning · Computer Science 2017-06-01 Marc G. Bellemare , Ivo Danihelka , Will Dabney , Shakir Mohamed , Balaji Lakshminarayanan , Stephan Hoyer , Rémi Munos

Our universe hosts various large-scale structures from voids to galaxy clusters, so it would be interesting to find some simple and reasonable measure to describe the inhomogeneities in the universe. We explore two different methods for…

General Relativity and Quantum Cosmology · Physics 2015-03-18 Nan Li , Xiao-Long Li , Shu-Peng Song

A common feature of methods for analyzing samples of probability density functions is that they respect the geometry inherent to the space of densities. Once a metric is specified for this space, the Fr\'echet mean is typically used to…

Methodology · Statistics 2018-12-20 Alexander Petersen , Hans-Georg Müller

We study the large deviation rate functional for the empirical distribution of independent Brownian particles with drift. In one dimension, it has been shown by Adams, Dirr, Peletier and Zimmer that this functional is asymptotically…

Probability · Mathematics 2016-01-11 Matthias Erbar , Jan Maas , Michiel Renger

The sliced-Wasserstein flow is an evolution equation where a probability density evolves in time, advected by a velocity field computed as the average among directions in the unit sphere of the optimal transport displacements from its 1D…

Optimization and Control · Mathematics 2024-05-13 Giacomo Cozzi , Filippo Santambogio

For two probability measures $\rho$ and $\pi$ with analytic densities on the $d$-dimensional cube $[-1,1]^d$, we investigate the approximation of the unique triangular monotone Knothe-Rosenblatt transport $T:[-1,1]^d\to [-1,1]^d$, such that…

Numerical Analysis · Mathematics 2021-07-29 Jakob Zech , Youssef Marzouk

We propose a model of optimal parallel transport between vector fields on a connection graph, which consists of a weighted graph along with a map from its edges to an orthogonal group. Inspired by the well-known equivalence of 1-Wasserstein…

Optimization and Control · Mathematics 2025-03-18 Sawyer Robertson , Dhruv Kohli , Gal Mishne , Alexander Cloninger

We generalize Einstein's probabilistic method for the Brownian motion to study compressible fluids in porous media. The multi-dimensional case is considered with general probability distribution functions. By relating the expected…

Analysis of PDEs · Mathematics 2025-03-06 Luan Hoang , Akif Ibragimov

We study heat conduction and momentum transport in the context of stochastic fluid dynamics. We consider a fluid described by model H in the classification of Hohenberg and Halperin. We study both non-critical and critical fluids, and we…

Nuclear Theory · Physics 2025-12-03 Chandrodoy Chattopadhyay , Josh Ott , Thomas Schaefer , Vladimir V. Skokov

We resolve a conjecture of De Palma and Trevisan by proving the triangle inequality for a quantum 2-Wasserstein distance. The proof relies on complex analysis methods to establish a new integral representation of the cost in the optimal…

Mathematical Physics · Physics 2025-11-26 Melchior Wirth

We prove existence and uniqueness of solutions to a transport equation modelling vehicular traffic in which the velocity field depends non-locally on the downstream traffic density via a discontinuous anisotropic kernel. The result is…

Analysis of PDEs · Mathematics 2015-10-16 Paola Goatin , Francesco Rossi

We derive transport-entropy inequalities for mixed binomial point processes, and for Poisson point processes. We show that when the finite intensity measure satisfies a Talagrand transport inequality, the law of the point process also…

Probability · Mathematics 2024-06-21 Nathael Gozlan , Ronan Herry , Giovanni Peccati

The late-time dynamics of quantum many-body systems is organized in distinct dynamical universality classes, characterized by their conservation laws and thus by their emergent hydrodynamic transport. Here, we study transport in the…

Quantum Gases · Physics 2022-08-30 Philip Zechmann , Alvise Bastianello , Michael Knap

We develop a novel stability theory for Sinkhorn semigroups based on Lyapunov techniques and quantitative contraction coefficients, and establish exponential convergence of Sinkhorn iterations on weighted Banach spaces. This…

Probability · Mathematics 2026-01-28 O. Deniz Akyildiz , Pierre del Moral , Joaquin Miguez
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