Suivre
arthur aubret
arthur aubret
Adresse e-mail validée de univ-lyon1.fr
Titre
Citée par
Citée par
Année
A survey on intrinsic motivation in reinforcement learning
A Aubret, L Matignon, S Hassas
arXiv preprint arXiv:1908.06976, 2019
1652019
An information-theoretic perspective on intrinsic motivation in reinforcement learning: A survey
A Aubret, L Matignon, S Hassas
Entropy 25 (2), 327, 2023
212023
Time to augment self-supervised visual representation learning
A Aubret, M Ernst, C Teulière, J Triesch
arXiv preprint arXiv:2207.13492, 2022
82022
ELSIM: End-to-end learning of reusable skills through intrinsic motivation
A Aubret, L Matignon, S Hassas
Machine Learning and Knowledge Discovery in Databases: European Conference …, 2021
62021
Mimo: A multi-modal infant model for studying cognitive development in humans and ais
D Mattern, FM López, MR Ernst, A Aubret, J Triesch
2022 IEEE International Conference on Development and Learning (ICDL), 23-29, 2022
52022
A survey on intrinsic motivation in reinforcement learning. arXiv
A Aubret, L Matignon, S Hassas
Preprint, 2019
52019
A survey on intrinsic motivation in reinforcement learning. arXiv 2019
A Aubret, L Matignon, S Hassas
arXiv preprint arXiv:1908.06976, 0
5
DisTop: Discovering a Topological representation to learn diverse and rewarding skills
A Aubret, L Matignon, S Hassas
IEEE Transactions on Cognitive and Developmental Systems, 2023
32023
MIMo: A Multi-Modal Infant Model for Studying Cognitive Development
D Mattern, P Schumacher, FM López, MC Raabe, MR Ernst, A Aubret, ...
IEEE Transactions on Cognitive and Developmental Systems, 2024
22024
Toddler-inspired embodied vision for learning object representations
A Aubret, C Teulièr, J Triesch
2022 IEEE International Conference on Development and Learning (ICDL), 81-87, 2022
22022
An information-theoretic perspective on intrinsic motivation in reinforcement learning
A Aubret, L Matignon, S Hassas
NeurIPS 2022 Workshop on Information-Theoretic Principles in Cognitive Systems, 2022
12022
Toddler-inspired learning induces hierarchical object representations
A Aubret, C Teulière, J Triesch
IEEE ICDL-Sensorimotor Interaction, language, and Embodiement of Symbols …, 2022
12022
Embodied vision for learning object representations
A Aubret, C Teulière, J Triesch
arXiv preprint arXiv:2205.06198, 2022
12022
Learning increasingly complex skills through deep reinforcement learning using intrinsic motivation
A Aubret
Université de Lyon, 2021
12021
Self-Supervised Learning of Color Constancy
MR Ernst, FM López, A Aubret, RW Fleming, J Triesch
arXiv preprint arXiv:2404.08127, 2024
2024
Caregiver Talk Shapes Toddler Vision: A Computational Study of Dyadic Play
T Schaumlöffel, A Aubret, G Roig, J Triesch
2023 IEEE International Conference on Development and Learning (ICDL), 67-72, 2023
2023
Compressed information is all you need: unifying intrinsic motivations and representation learning
A Aubret, M Lefort, C Teulière, L Matignon, S Hassas, J Triesch
NeurIPS 2022 Workshop on Information-Theoretic Principles in Cognitive Systems, 2022
2022
Apprentissage de compétences de plus en plus complexes via l'apprentissage profond par renforcement en utilisant la motivation intrinsèque
A Aubret
2021
Apprentissage séquentiel de compétences via la motivation intrinsèque et l'apprentissage par renforcement
H Bonnavaud, A Aubret, L Matignon
Université Lyon 1, 2021
2021
Étude de la motivation intrinsèque en apprentissage par renforcement
A Aubret, L Matignon, S Hassas
Journées Francophones sur la Planification, la Décision et l'Apprentissage …, 2019
2019
Le système ne peut pas réaliser cette opération maintenant. Veuillez réessayer plus tard.
Articles 1–20