19 citations · 48 across the 13 of their papers we have counts for
13 papers
A New Perspective on Precision and Recall for Generative Models
Benjamin Sykes, Loïc Simon, Julien Rabin +1
With the recent success of generative models in image and text, the question of their evaluation has recently gained a lot of attention. While most methods from the state of the ar…
Unifying and extending Precision Recall metrics for assessing generative models
Benjamin Sykes, Loic Simon, Julien Rabin
With the recent success of generative models in image and text, the evaluation of generative models has gained a lot of attention. Whereas most generative models are compared in te…
On the De-duplication of LAION-2B
Ryan Webster, Julien Rabin, Loic Simon +1
Generative models, such as DALL-E, Midjourney, and Stable Diffusion, have societal implications that extend beyond the field of computer science. These models require large image d…
Adversarial Counterfactual Visual Explanations
Guillaume Jeanneret, Loïc Simon, Frédéric Jurie
Counterfactual explanations and adversarial attacks have a related goal: flipping output labels with minimal perturbations regardless of their characteristics. Yet, adversarial att…
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…
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…