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David Filliat
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Publications
- 2020
- [j17]Timothée Lesort, Vincenzo Lomonaco, Andrei Stoian, Davide Maltoni, David Filliat, Natalia Díaz Rodríguez:
Continual learning for robotics: Definition, framework, learning strategies, opportunities and challenges. Inf. Fusion 58: 52-68 (2020) - 2019
- [j16]Céline Craye, Timothée Lesort, David Filliat, Jean-François Goudou:
Exploring to learn visual saliency: The RL-IAC approach. Robotics Auton. Syst. 112: 244-259 (2019) - [c51]Timothée Lesort, Alexander Gepperth, Andrei Stoian, David Filliat:
Marginal Replay vs Conditional Replay for Continual Learning. ICANN (2) 2019: 466-480 - [c50]Timothée Lesort, Andrei Stoian, Jean-François Goudou, David Filliat:
Training Discriminative Models to Evaluate Generative Ones. ICANN (3) 2019: 604-619 - [c49]Timothée Lesort, Hugo Caselles-Dupré, Michaël Garcia Ortiz, Andrei Stoian, David Filliat:
Generative Models from the perspective of Continual Learning. IJCNN 2019: 1-8 - [c48]Timothée Lesort, Mathieu Seurin, Xinrui Li, Natalia Díaz Rodríguez, David Filliat:
Deep unsupervised state representation learning with robotic priors: a robustness analysis. IJCNN 2019: 1-8 - [i22]Antonin Raffin, Ashley Hill, Kalifou René Traoré, Timothée Lesort, Natalia Díaz Rodríguez, David Filliat:
Decoupling feature extraction from policy learning: assessing benefits of state representation learning in goal based robotics. CoRR abs/1901.08651 (2019) - [i19]René Traoré, Hugo Caselles-Dupré, Timothée Lesort, Te Sun, Natalia Díaz Rodríguez, David Filliat:
Continual Reinforcement Learning deployed in Real-life using Policy Distillation and Sim2Real Transfer. CoRR abs/1906.04452 (2019) - [i18]Timothée Lesort, Vincenzo Lomonaco, Andrei Stoian, Davide Maltoni, David Filliat, Natalia Díaz Rodríguez:
Continual Learning for Robotics. CoRR abs/1907.00182 (2019) - [i17]René Traoré, Hugo Caselles-Dupré, Timothée Lesort, Te Sun, Guanghang Cai, Natalia Díaz Rodríguez, David Filliat:
DisCoRL: Continual Reinforcement Learning via Policy Distillation. CoRR abs/1907.05855 (2019) - [i16]Timothée Lesort, Andrei Stoian, David Filliat:
Regularization Shortcomings for Continual Learning. CoRR abs/1912.03049 (2019) - 2018
- [j13]Timothée Lesort, Natalia Díaz Rodríguez, Jean-François Goudou, David Filliat:
State representation learning for control: An overview. Neural Networks 108: 379-392 (2018) - [i15]Timothée Lesort, Natalia Díaz Rodríguez, Jean-François Goudou, David Filliat:
State Representation Learning for Control: An Overview. CoRR abs/1802.04181 (2018) - [i14]Céline Craye, Timothée Lesort, David Filliat, Jean-Francois Goudou:
Exploring to learn visual saliency: The RL-IAC approach. CoRR abs/1804.00435 (2018) - [i13]Timothée Lesort, Jean-François Goudou, David Filliat:
Training Discriminative Models to Evaluate Generative Ones. CoRR abs/1806.10840 (2018) - [i8]Antonin Raffin, Ashley Hill, René Traoré, Timothée Lesort, Natalia Díaz Rodríguez, David Filliat:
S-RL Toolbox: Environments, Datasets and Evaluation Metrics for State Representation Learning. CoRR abs/1809.09369 (2018) - [i6]Timothée Lesort, Alexander Gepperth, Andrei Stoian, David Filliat:
Marginal Replay vs Conditional Replay for Continual Learning. CoRR abs/1810.12069 (2018) - [i4]Timothée Lesort, Hugo Caselles-Dupré, Michaël Garcia Ortiz, Andrei Stoian, David Filliat:
Generative Models from the perspective of Continual Learning. CoRR abs/1812.09111 (2018) - 2017
- [i3]Timothée Lesort, Mathieu Seurin, Xinrui Li, Natalia Díaz Rodríguez, David Filliat:
Unsupervised state representation learning with robotic priors: a robustness benchmark. CoRR abs/1709.05185 (2017)
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