activity
20152022
most citedAn Adversarial Regularisation for Semi-Supervised Training of Structured Output Neural Networks

19 citations · 47 across the 10 of their papers we have counts for

collaborators

26 papers

cs.SE2022

Empowering the trustworthiness of ML-based critical systems through engineering activities

Juliette Mattioli, Agnes Delaborde, Souhaiel Khalfaoui +3

This paper reviews the entire engineering process of trustworthy Machine Learning (ML) algorithms designed to equip critical systems with advanced analytics and decision functions.…

cs.CV20227 cited

Diffusion Models for Counterfactual Explanations

Guillaume Jeanneret, Loïc Simon, Frédéric Jurie

Counterfactual explanations have shown promising results as a post-hoc framework to make image classifiers more explainable. In this paper, we propose DiME, a method allowing the g…

cs.LG2021

On the inductive biases of deep domain adaptation

Rodrigue Siry, Louis Hémadou, Loïc Simon +1

Domain alignment is currently the most prevalent solution to unsupervised domain-adaptation tasks and are often being presented as minimizers of some theoretical upper-bounds on ri…

cs.CV2021

Training face verification models from generated face identity data

Dennis Conway, Loic Simon, Alexis Lechervy +1

Machine learning tools are becoming increasingly powerful and widely used. Unfortunately membership attacks, which seek to uncover information from data sets used in machine learni…

cs.CV202115 cited

This Person (Probably) Exists. Identity Membership Attacks Against GAN Generated Faces

Ryan Webster, Julien Rabin, Loic Simon +1

Recently, generative adversarial networks (GANs) have achieved stunning realism, fooling even human observers. Indeed, the popular tongue-in-cheek website {\small \url{ http://this…

cs.LG20195 cited

Towards a General Model of Knowledge for Facial Analysis by Multi-Source Transfer Learning

Valentin Vielzeuf, Alexis Lechervy, Stéphane Pateux +1

This paper proposes a step toward obtaining general models of knowledge for facial analysis, by addressing the question of multi-source transfer learning. More precisely, the propo…