no code implementations • 29 Sep 2021 • Raphaël Jean, Pierre-Luc St-Charles, Soren Pirk, Simon Brodeur
Our goal is to show that common Siamese networks can effectively be trained on video sequences to disentangle attributes related to pose and motion that are useful for video and non-video tasks, yet typically suppressed in usual training schemes.
no code implementations • 1 Jan 2021 • Luca Celotti, Simon Brodeur, Jean Rouat
Then, we benchmark on a real dataset of human dialogues.
no code implementations • 30 Mar 2020 • Luca Celotti, Simon Brodeur, Jean Rouat
This partially supports to the hypothesis that encoding information into volumes instead of into points, can lead to improved retrieval of learned information with random sampling.
no code implementations • 5 Nov 2019 • Luca Celotti, Simon Brodeur, Jean Rouat
While it is known that those embeddings are able to learn some structures of language (e. g. grammar) in a purely data-driven manner, there is very little work on the objective evaluation of their ability to cover the whole language space and to generalize to sentences outside the language bias of the training data.
no code implementations • 27 Apr 2018 • Marc-Antoine Moinnereau, Thomas Brienne, Simon Brodeur, Jean Rouat, Kevin Whittingstall, Eric Plourde
The use of electroencephalogram (EEG) as the main input signal in brain-machine interfaces has been widely proposed due to the non-invasive nature of the EEG.
no code implementations • 29 Nov 2017 • Simon Brodeur, Ethan Perez, Ankesh Anand, Florian Golemo, Luca Celotti, Florian Strub, Jean Rouat, Hugo Larochelle, Aaron Courville
We introduce HoME: a Household Multimodal Environment for artificial agents to learn from vision, audio, semantics, physics, and interaction with objects and other agents, all within a realistic context.
1 code implementation • Artificial Neural Networks and Machine Learning – ICANN 2012 • Simon Brodeur, Jean Rouat
This is due to the extremely non-linear dynamics of recurrent spiking neural networks.