Corentin Tallec
Corentin Tallec
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Bootstrap your own latent-a new approach to self-supervised learning
JB Grill, F Strub, F Altché, C Tallec, P Richemond, E Buchatskaya, ...
Advances in neural information processing systems 33, 21271-21284, 2020
Can recurrent neural networks warp time?
C Tallec, Y Ollivier
arXiv preprint arXiv:1804.11188, 2018
Unbiased online recurrent optimization
C Tallec, Y Ollivier
arXiv preprint arXiv:1702.05043, 2017
Unbiasing truncated backpropagation through time
C Tallec, Y Ollivier
arXiv preprint arXiv:1705.08209, 2017
Bootstrapped representation learning on graphs
S Thakoor, C Tallec, MG Azar, R Munos, P Veličković, M Valko
ICLR 2021 Workshop on Geometrical and Topological Representation Learning, 2021
Creating artificial human genomes using generative neural networks
B Yelmen, A Decelle, L Ongaro, D Marnetto, C Tallec, F Montinaro, ...
PLoS genetics 17 (2), e1009303, 2021
Making deep q-learning methods robust to time discretization
C Tallec, L Blier, Y Ollivier
International Conference on Machine Learning, 6096-6104, 2019
Broaden your views for self-supervised video learning
A Recasens, P Luc, JB Alayrac, L Wang, F Strub, C Tallec, M Malinowski, ...
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021
Training recurrent networks online without backtracking
Y Ollivier, C Tallec, G Charpiat
arXiv preprint arXiv:1507.07680, 2015
BYOL works even without batch statistics
PH Richemond, JB Grill, F Altché, C Tallec, F Strub, A Brock, S Smith, ...
arXiv preprint arXiv:2010.10241, 2020
Mixed batches and symmetric discriminators for GAN training
T Lucas, C Tallec, Y Ollivier, J Verbeek
International Conference on Machine Learning, 2844-2853, 2018
Large-scale representation learning on graphs via bootstrapping
S Thakoor, C Tallec, MG Azar, M Azabou, EL Dyer, R Munos, P Veličković, ...
arXiv preprint arXiv:2102.06514, 2021
Shaking the foundations: delusions in sequence models for interaction and control
PA Ortega, M Kunesch, G Delétang, T Genewein, J Grau-Moya, J Veness, ...
arXiv preprint arXiv:2110.10819, 2021
Learning successor states and goal-dependent values: A mathematical viewpoint
L Blier, C Tallec, Y Ollivier
arXiv preprint arXiv:2101.07123, 2021
Emergent communication at scale
R Chaabouni, F Strub, F Altché, E Tarassov, C Tallec, E Davoodi, ...
International Conference on Learning Representations, 2021
Density-Based Bonuses on Learned Representations for Reward-Free Exploration in Deep Reinforcement Learning
OD Domingues, C Tallec, R Munos, M Valko
ICML 2021 Workshop on Unsupervised Reinforcement Learning, 2021
BYOL-Explore: Exploration by Bootstrapped Prediction
ZD Guo, S Thakoor, M Pîslar, BA Pires, F Altché, C Tallec, A Saade, ...
arXiv preprint arXiv:2206.08332, 2022
Self-supervised representation learning using bootstrapped latent representations
JBFL Grill, F Strub, F Altché, C Tallec, P Richemond, BA Pires, Z Guo, ...
US Patent App. 17/338,777, 2021
Recurrent Neural Networks and Reinforcement Learning: Dynamic Approaches
C Tallec
Université Paris-Saclay, 2019
Recurrent Neural Networks and Reinforcement Learning: Dynamic Approaches.(Réseaux Récurrents et Apprentissage par Renforcement: Approches Dynamiques)
C Tallec
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