25 citations · 80 across the 11 of their papers we have counts for
4 papers · 1 filter
Variational models for signal processing with Graph Neural Networks
Amitoz Azad, Julien Rabin, Abderrahim Elmoataz
This paper is devoted to signal processing on point-clouds by means of neural networks. Nowadays, state-of-the-art in image processing and computer vision is mostly based on traini…
On the Theoretical Equivalence of Several Trade-Off Curves Assessing Statistical Proximity
Rodrigue Siry, Ryan Webster, Loic Simon +1
The recent advent of powerful generative models has triggered the renewed development of quantitative measures to assess the proximity of two probability distributions. As the scal…
Revisiting Precision and Recall Definition for Generative Model Evaluation
Loïc Simon, Ryan Webster, Julien Rabin
In this article we revisit the definition of Precision-Recall (PR) curves for generative models proposed by Sajjadi et al. (arXiv:1806.00035). Rather than providing a scalar for ge…
Detecting Overfitting of Deep Generative Networks via Latent Recovery
Ryan Webster, Julien Rabin, Loic Simon +1
State of the art deep generative networks are capable of producing images with such incredible realism that they can be suspected of memorizing training images. It is why it is not…