12 citations · 13 across the 10 of their papers we have counts for
9 papers · 1 filter
From plans to maps: Nonlocal regularization of optimal transport
Marcello Carioni, Leonardo Del Grande, José A. Iglesias +1
We introduce a nonlocal regularization of optimal transport that bridges Kantorovich and Monge formulations. The regularization penalizes oscillations through an interaction kernel…
A Distributionally Robust Framework for Learned Reconstructions in Inverse Problems
Floor van Maarschalkerwaart, Subhadip Mukherjee, Christoph Brune +1
Learned reconstruction operators for inverse problems are typically trained under a fixed noise model, and generalize poorly when the distribution during testing differs from the o…
Atomic Gradient Flows: Gradient Flows on Sparse Representations
Christian Amend, Marcello Carioni, Konstantinos Zemas
One of the most popular approaches for solving total variation-regularized optimization problems in the space of measures are Particle Gradient Flows (PGFs). These restrict the pro…
A Dual Certificate Approach to Sparsity in Infinite-Width Shallow Neural Networks
Leonardo Del Grande, Christoph Brune, Marcello Carioni
In this paper, we study total variation (TV)-regularized training of infinite-width shallow ReLU neural networks, formulated as a convex optimization problem over measures on the u…
Sparsity for dynamic inverse problems on Wasserstein curves with bounded variation
Marcello Carioni, Julius Lohmann
We investigate a dynamic inverse problem using a regularization which implements the so-called Wasserstein- distance. It naturally extends well-known static problems such as las…
Perturbation-Aware Distributionally Robust Optimization for Inverse Problems
Floor van Maarschalkerwaart, Subhadip Mukherjee, Malena Sabaté Landman +2
This paper builds on classical distributionally robust optimization techniques to construct a comprehensive framework that can be used for solving inverse problems. Given an estima…