Optimal transport is a long‐standing theory that has been studied in depth from both
theoretical and numerical point of views. Starting from the 50s this theory has also found a …

Mechanism Design seeks to establish protocols for aggregating the private information of a
set of agents to optimize a global objective. Nonetheless, optimizing a communal goal solely …

We investigate properties of some extensions of a class of Fourier-based probability metrics,
originally introduced to study convergence to equilibrium for the solution to the spatially …

This paper proposes an efficient HOT algorithm for solving the optimal transport (OT)
problems with finite supports. We particularly focus on an efficient implementation of the …

The term" Normalizing Flows" is related to the task of constructing invertible transport maps
between probability measures by means of deep neural networks. In this paper, we consider …

This paper presents a family of generative Linear Programming models that permit to
compute the exact Wasserstein Barycenter of a large set of two-dimensional images …

Autonomous systems comprised of many cooperative agents have the potential for enabling
long-duration tasks and data collection critical to the understanding of a wide range of …

Inequity is one of the primary economic and societal risks posed by the global food system,
yet measures of inequity are missing from prominent corporate tools that aim to account for …

In this paper, we investigate the k-Facility Location Problem (k-FLP) within the Bayesian
Mechanism Design framework, in which agents' preferences are samples of a probability …

In this note, we show that the squared Wasserstein distance can be expressed as the
average over the sphere of one dimensional Wasserstein distances. We name this new …