Timothée Lesort

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 38

Top Topics

Reinforcement Learning

Visual Saliency

Feature Relevance

Top Venues

Publications

Mohammad-Javad Darvishi Bayazi, Mohammad Sajjad Ghaemi, Timothée Lesort, Md Rifat Arefin, Jocelyn Faubert, Irina Rish
Amplifying pathological detection in EEG signaling pathways through cross-dataset transfer learning. Comput. Biol. Medicine 169 (2024)
Adam Ibrahim, Benjamin Thérien, Kshitij Gupta, Mats L. Richter, Quentin Gregory Anthony, Eugene Belilovsky, Timothée Lesort, Irina Rish
Simple and Scalable Strategies to Continually Pre-train Large Language Models. Trans. Mach. Learn. Res. 2024 (2024)
Adam Ibrahim, Benjamin Thérien, Kshitij Gupta, Mats L. Richter, Quentin Anthony, Timothée Lesort, Eugene Belilovsky, Irina Rish
Simple and Scalable Strategies to Continually Pre-train Large Language Models. CoRR (2024)
Evangelia Gogoulou, Timothée Lesort, Magnus Boman, Joakim Nivre
A Study of Continual Learning Under Language Shift. CoRR (2023)
Timothée Lesort
Spurious Features in Continual Learning. AAAI Bridge Program (2023)
Mohammad-Javad Darvishi Bayazi, Mohammad Sajjad Ghaemi, Timothée Lesort, Md Rifat Arefin, Jocelyn Faubert, Irina Rish
Amplifying Pathological Detection in EEG Signaling Pathways through Cross-Dataset Transfer Learning. CoRR (2023)
Timothée Lesort, Oleksiy Ostapenko, Pau Rodríguez, Diganta Misra, Md Rifat Arefin, Laurent Charlin, Irina Rish
Challenging Common Assumptions about Catastrophic Forgetting and Knowledge Accumulation. CoLLAs (2023)
Kshitij Gupta, Benjamin Thérien, Adam Ibrahim, Mats L. Richter, Quentin Anthony, Eugene Belilovsky, Irina Rish, Timothée Lesort
Continual Pre-Training of Large Language Models: How to (re)warm your model? CoRR (2023)
Benedikt Bagus, Alexander Gepperth, Timothée Lesort
Beyond Supervised Continual Learning: a Review. CoRR (2022)
Oleksiy Ostapenko, Timothée Lesort, Pau Rodríguez, Md Rifat Arefin, Arthur Douillard, Irina Rish, Laurent Charlin
Continual Learning with Foundation Models: An Empirical Study of Latent Replay. CoLLAs (2022)
Timothée Lesort, Oleksiy Ostapenko, Diganta Misra, Md Rifat Arefin, Pau Rodríguez, Laurent Charlin, Irina Rish
Scaling the Number of Tasks in Continual Learning. CoRR (2022)
Timothée Lesort
Continual Feature Selection: Spurious Features in Continual Learning. CoRR (2022)
Alexander Gepperth, Timothée Lesort
Tutorial - Continual Learning beyond classification. ESANN (2022)
Oleksiy Ostapenko, Timothée Lesort, Pau Rodríguez, Md Rifat Arefin, Arthur Douillard, Irina Rish, Laurent Charlin
Foundational Models for Continual Learning: An Empirical Study of Latent Replay. CoRR (2022)
Timothée Lesort, Massimo Caccia, Irina Rish
Understanding Continual Learning Settings with Data Distribution Drift Analysis. CoRR (2021)
Timothée Lesort, Thomas George, Irina Rish
Continual Learning in Deep Networks: an Analysis of the Last Layer. CoRR (2021)
Fabrice Normandin, Florian Golemo, Oleksiy Ostapenko, Pau Rodríguez, Matthew D. Riemer, Julio Hurtado, Khimya Khetarpal, Dominic Zhao, Ryan Lindeborg, Timothée Lesort, Laurent Charlin, Irina Rish, Massimo Caccia
Sequoia: A Software Framework to Unify Continual Learning Research. CoRR (2021)
Arthur Douillard, Timothée Lesort
Continuum: Simple Management of Complex Continual Learning Scenarios. CoRR (2021)
Timothée Lesort
Continual Learning: Tackling Catastrophic Forgetting in Deep Neural Networks with Replay Processes. CoRR (2020)
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 (2020)
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 (2019)
Timothée Lesort, Vincenzo Lomonaco, Andrei Stoian, Davide Maltoni, David Filliat, Natalia Díaz Rodríguez
Continual Learning for Robotics. CoRR (2019)
Timothée Lesort, Andrei Stoian, David Filliat
Regularization Shortcomings for Continual Learning. CoRR (2019)
Timothée Lesort, Mathieu Seurin, Xinrui Li, Natalia Díaz Rodríguez, David Filliat
Deep unsupervised state representation learning with robotic priors: a robustness analysis. IJCNN (2019)
Timothée Lesort, Andrei Stoian, Jean-François Goudou, David Filliat
Training Discriminative Models to Evaluate Generative Ones. ICANN (3) (2019)
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 (2019)
René Traoré, Hugo Caselles-Dupré, Timothée Lesort, Te Sun, Guanghang Cai, Natalia Díaz Rodríguez, David Filliat
DisCoRL: Continual Reinforcement Learning via Policy Distillation. CoRR (2019)
Céline Craye, Timothée Lesort, David Filliat, Jean-François Goudou
Exploring to learn visual saliency: The RL-IAC approach. Robotics Auton. Syst. 112 (2019)
Timothée Lesort, Alexander Gepperth, Andrei Stoian, David Filliat
Marginal Replay vs Conditional Replay for Continual Learning. ICANN (2) (2019)
Timothée Lesort, Hugo Caselles-Dupré, Michaël Garcia Ortiz, Andrei Stoian, David Filliat
Generative Models from the perspective of Continual Learning. IJCNN (2019)
Timothée Lesort, Alexander Gepperth, Andrei Stoian, David Filliat
Marginal Replay vs Conditional Replay for Continual Learning. CoRR (2018)
Timothée Lesort, Natalia Díaz Rodríguez, Jean-François Goudou, David Filliat
State Representation Learning for Control: An Overview. CoRR (2018)
Timothée Lesort, Hugo Caselles-Dupré, Michaël Garcia Ortiz, Andrei Stoian, David Filliat
Generative Models from the perspective of Continual Learning. CoRR (2018)
Timothée Lesort, Jean-François Goudou, David Filliat
Training Discriminative Models to Evaluate Generative Ones. CoRR (2018)
Timothée Lesort, Natalia Díaz Rodríguez, Jean-François Goudou, David Filliat
State representation learning for control: An overview. Neural Networks 108 (2018)
Céline Craye, Timothée Lesort, David Filliat, Jean-Francois Goudou
Exploring to learn visual saliency: The RL-IAC approach. CoRR (2018)
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 (2018)
Timothée Lesort, Mathieu Seurin, Xinrui Li, Natalia Díaz Rodríguez, David Filliat
Unsupervised state representation learning with robotic priors: a robustness benchmark. CoRR (2017)