Mathieu Lefort

According to our database, Mathieu Lefort authored at least 30 papers between 2011 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2023

Sequential annotations for naturally-occurring HRI: first insights.

Lucien Tisserand, Frédéric Armetta, Heike Baldauf-Quilliatre, Antoine Bouquin, Salima Hassas, Mathieu Lefort

CoRR, 2023

Understanding the Usages and Effects of a Recommendation System in a Non-formal Learning Context.

Anaëlle Badier, Mathieu Lefort, Marie Lefèvre

Proceedings of the Augmented Intelligence and Intelligent Tutoring Systems, 2023

EquiMod: An Equivariance Module to Improve Visual Instance Discrimination.

Alexandre Devillers, Mathieu Lefort

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Recommendation Model for an After-School E-learning Mobile Application.

Anaëlle Badier, Mathieu Lefort, Marie Lefèvre

Proceedings of the 15th International Conference on Computer Supported Education, 2023

L'apprentissage algorithmique, une nouvelle étape pour l'IA. Une application aux opérations arithmétiques.

Frédéric Armetta, Anthony Baccuet, Mathieu Lefort

Proceedings of the Conférence Nationale en Intelligence Artificielle, 2023

Champ neuronal et apprentissage profond de topologies pour la fusion multimodale.

Simon Forest, Jean-Charles Quinton, Mathieu Lefort

Proceedings of the Conférence Nationale en Intelligence Artificielle, 2023

2022

A Dynamic Neural Field Model of Multimodal Merging: Application to the Ventriloquist Effect.

Simon Forest, Jean-Charles Quinton, Mathieu Lefort

Neural Comput., 2022

EquiMod: An Equivariance Module to Improve Self-Supervised Learning.

Alexandre Devillers, Mathieu Lefort

CoRR, 2022

Combining Manifold Learning and Neural Field Dynamics for Multimodal Fusion.

Simon Forest, Jean-Charles Quinton, Mathieu Lefort

Proceedings of the International Joint Conference on Neural Networks, 2022

The Impact of Action in Visual Representation Learning.

Alexandre Devillers, Valentin Chaffraix, Frédéric Armetta, Stefan Duffner, Mathieu Lefort

Proceedings of the IEEE International Conference on Development and Learning, 2022

2021

Novelty detection for unsupervised continual learning in image sequences.

Ruiqi Dai, Mathieu Lefort, Frédéric Armetta, Mathieu Guillermin, Stefan Duffner

Proceedings of the 33rd IEEE International Conference on Tools with Artificial Intelligence, 2021

Self-supervised Continual Learning for Object Recognition in Image Sequences.

Ruiqi Dai, Mathieu Lefort, Frédéric Armetta, Mathieu Guillermin, Stefan Duffner

Proceedings of the Neural Information Processing - 28th International Conference, 2021

2020

Learning Arithmetic Operations With A Multistep Deep Learning.

Bastien Nollet, Mathieu Lefort, Frédéric Armetta

Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

2019

The RoPE Scale: a Measure of How Empathic a Robot is Perceived.

Laurianne Charrier, Alisa Rieger, Alexandre Galdeano, Amélie Cordier, Mathieu Lefort, Salima Hassas

Proceedings of the 14th ACM/IEEE International Conference on Human-Robot Interaction, 2019

2017

Ajustement diffus et adaptatif de la consommation électrique résidentielle par un système multi-agent auto-adaptatif.

Victor Lequay, Mathieu Lefort, Saber Mansour, Salima Hassas

Rev. d'Intelligence Artif., 2017

2016

Flexible Load Shedding Using Gossip Communication in a Multi-agents System.

Victor Lequay, Mathieu Lefort, Saber Mansour, Salima Hassas

Proceedings of the 10th IEEE International Conference on Self-Adaptive and Self-Organizing Systems, 2016

Ajustement Diffus et Adaptatif de la Consommation Électrique Résidentielle par un Système Multi-Agents.

Victor Lequay, Mathieu Lefort, Saber Mansour, Salima Hassas

Proceedings of the Systèmes Multi-Agents et simulation, 2016

Learning to be attractive: Probabilistic computation with dynamic attractor networks.

Alexander Gepperth, Mathieu Lefort

Proceedings of the 2016 Joint IEEE International Conference on Development and Learning and Epigenetic Robotics, 2016

2015

Learning of local predictable representations in partially learnable environments.

Mathieu Lefort, Alexander Gepperth

Proceedings of the 2015 International Joint Conference on Neural Networks, 2015

Active learning of local predictable representations with artificial curiosity.

Mathieu Lefort, Alexander Gepperth

Proceedings of the 2015 Joint IEEE International Conference on Development and Learning and Epigenetic Robotics, 2015

Biologically inspired incremental learning for high-dimensional spaces.

Alexander Gepperth, Thomas Hecht, Mathieu Lefort, Ursula Körner

Proceedings of the 2015 Joint IEEE International Conference on Development and Learning and Epigenetic Robotics, 2015

Using self-organizing maps for regression: the importance of the output function.

Thomas Hecht, Mathieu Lefort, Alexander Gepperth

Proceedings of the 23rd European Symposium on Artificial Neural Networks, 2015

Resource-efficient Incremental learning in very high dimensions.

Alexander Gepperth, Mathieu Lefort, Thomas Hecht

Proceedings of the 23rd European Symposium on Artificial Neural Networks, 2015

2014

PROPRE: PROjection and PREdiction for multimodal correlations learning. An application to pedestrians visual data discrimination.

Mathieu Lefort, Alexander Gepperth

Proceedings of the 2014 International Joint Conference on Neural Networks, 2014

Multimodal space representation driven by self-evaluation of predictability.

Mathieu Lefort, Thomas Kopinski, Alexander Gepperth

Proceedings of the 4th International Conference on Development and Learning and on Epigenetic Robotics, 2014

Latency-Based Probabilistic Information Processing in Recurrent Neural Hierarchies.

Alexander Gepperth, Mathieu Lefort

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2014, 2014

Discrimination of visual pedestrians data by combining projection and prediction learning.

Mathieu Lefort, Alexander Gepperth

Proceedings of the 22th European Symposium on Artificial Neural Networks, 2014

2013

SOMMA: Cortically inspired paradigms for multimodal processing.

Mathieu Lefort, Yann Boniface, Bernard Girau

Proceedings of the 2013 International Joint Conference on Neural Networks, 2013

2012

Apprentissage spatial de corrélations multimodales par des mécanismes d'inspiration corticale. (Spatial learning of multimodal correlations in a cortically inspired way).

Mathieu Lefort

PhD thesis, 2012

2011

Unlearning in the BCM Learning Rule for Plastic Self-organization in a Multi-modal Architecture.

Mathieu Lefort, Yann Boniface, Bernard Girau

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2011, 2011