In this paper, we investigate the impact of test-time adversarial attack...
The relevance of optimal transport methods to machine learning has long ...
In this note, we propose polynomial-time algorithms solving the Monge an...
In this work we study the robustness to adversarial attacks, of
early-st...
The matching principles behind optimal transport (OT) play an increasing...
Triangular flows, also known as Knöthe-Rosenblatt measure couplings,
com...
We propose a new computationally efficient test for conditional independ...
The ability to compare and align related datasets living in heterogeneou...
Several recent applications of optimal transport (OT) theory to machine
...
This paper tackles the problem of adversarial examples from a game theor...
We introduce an extension of the optimal transportation (OT) problem whe...
Although Sinkhorn divergences are now routinely used in data sciences to...
We consider convolutional networks from a reproducing kernel Hilbert spa...
We characterize the behavior of integral operators associated with
multi...
This work considers noise removal from images, focusing on the well know...