no code implementations • CVPR 2023 • Thomas Fel, Melanie Ducoffe, David Vigouroux, Remi Cadene, Mikael Capelle, Claire Nicodeme, Thomas Serre
A variety of methods have been proposed to try to explain how deep neural networks make their decisions.
no code implementations • 5 May 2020 • Olga Fink, Qin Wang, Markus Svensén, Pierre Dersin, Wan-Jui Lee, Melanie Ducoffe
Deep learning applications have been thriving over the last decade in many different domains, including computer vision and natural language understanding.
no code implementations • ACL 2018 • Laurent Vanni, Melanie Ducoffe, Carlos Aguilar, Frederic Precioso, Damon Mayaffre
In this paper, we propose a new strategy, called Text Deconvolution Saliency (TDS), to visualize linguistic information detected by a CNN for text classification.
no code implementations • 27 Feb 2018 • Melanie Ducoffe, Frederic Precioso
We propose a new active learning strategy designed for deep neural networks.
no code implementations • 19 Nov 2015 • Melanie Ducoffe, Frederic Precioso
While the current trend is to increase the depth of neural networks to increase their performance, the size of their training database has to grow accordingly.