activity
20192022
most citedLearning normalizing flows from Entropy-Kantorovich potentials

4 citations · 6 across the 5 of their papers we have counts for

collaborators

6 papers

math.PR20221 cited

An entropic generalization of Caffarelli's contraction theorem via covariance inequalities

Sinho Chewi, Aram-Alexandre Pooladian

The optimal transport map between the standard Gaussian measure and an -strongly log-concave probability measure is -Lipschitz, as first observed in a celebrated theor…

math.OC2020

A Study of One-Parameter Regularization Methods for Mathematical Programs with Vanishing Constraints

Tim Hoheisel, Blanca Pablos, Aram-Alexandre Pooladian +2

Mathematical programs with vanishing constraints (MPVCs) are a class of nonlinear optimization problems with applications to various engineering problems such as truss topology des…

cs.LG20204 cited

Learning normalizing flows from Entropy-Kantorovich potentials

Chris Finlay, Augusto Gerolin, Adam M Oberman +1

We approach the problem of learning continuous normalizing flows from a dual perspective motivated by entropy-regularized optimal transport, in which continuous normalizing flows a…

cs.LG2019

Farkas layers: don't shift the data, fix the geometry

Aram-Alexandre Pooladian, Chris Finlay, Adam M Oberman

Successfully training deep neural networks often requires either batch normalization, appropriate weight initialization, both of which come with their own challenges. We propose an…

cs.LG2019

A principled approach for generating adversarial images under non-smooth dissimilarity metrics

Aram-Alexandre Pooladian, Chris Finlay, Tim Hoheisel +1

Deep neural networks perform well on real world data but are prone to adversarial perturbations: small changes in the input easily lead to misclassification. In this work, we propo…

cs.LG20191 cited

The LogBarrier adversarial attack: making effective use of decision boundary information

Chris Finlay, Aram-Alexandre Pooladian, Adam M. Oberman

Adversarial attacks for image classification are small perturbations to images that are designed to cause misclassification by a model. Adversarial attacks formally correspond to a…