Outline
My Papers
- Continual Learning: Tackling Catastrophic Forgetting in Deep Neural Networks with Replay Processes, (2020) [paper] [bib] by Timothée Lesort
- Continual learning for robotics: Definition, framework, learning strategies, opportunities and challenges, (2020) [paper] [bib] by Timothée Lesort, Vincenzo Lomonaco, Andrei Stoian, Davide Maltoni, David Filliat and Natalia Díaz-Rodríguez
- Generative Models from the perspective of Continual Learning, (2019) [paper] [bib] by Lesort, Timoth{'e}e, Caselles-Dupr{'e}, Hugo, Garcia-Ortiz, Michael, Goudou, Jean-Fran{\c c}ois and Filliat, David
- DisCoRL: Continual Reinforcement Learning via Policy Distillation, (2019) [paper] [bib] by Ren{'{e}} Traor{'{e}} and Hugo Caselles{-}Dupr{'{e}} and Timoth{'{e}}e Lesort and Te Sun and Guanghang Cai and Natalia D{'{\i}}az Rodr{'{\i}}guez and David Filliat
- Continual Reinforcement Learning deployed in Real-life using PolicyDistillation and Sim2Real Transfer, (2019) [bib] by *Kalifou, René Traoré, Caselles-Dupré, Hugo, Lesort, Timothée, Sun, Te, Diaz-Rodriguez, Natalia and Filliat, David *
- Marginal replay vs conditional replay for continual learning, (2019) [paper] [bib] by Lesort, Timoth{'e}e, Gepperth, Alexander, Stoian, Andrei and Filliat, David
- Regularization Shortcomings for Continual Learning, (2019) [bib] by Lesort, Timoth{'e}e, Stoian, Andrei and Filliat, David