Unsupervised state representation learning with robotic priors: a robustness benchmark. - Timothée Lesort; Mathieu Seurin; Xinrui Li; Natalia Díaz Rodríguez; David Filliat (CoRR, 2017)

Training Discriminative Models to Evaluate Generative Ones. - Timothée Lesort; Jean-François Goudou; David Filliat (CoRR, 2018)

S-RL Toolbox: Environments, Datasets and Evaluation Metrics for State Representation Learning. - Antonin Raffin; Ashley Hill; René Traoré; Timothée Lesort; Natalia Díaz Rodríguez; David Filliat (CoRR, 2018)

State representation learning for control: An overview. - Timothée Lesort; Natalia Díaz Rodríguez; Jean-François Goudou; David Filliat (Neural Networks, 2018)

Marginal Replay vs Conditional Replay for Continual Learning. - Timothée Lesort; Alexander Gepperth; Andrei Stoian; David Filliat (ICANN (2), 2019)

Training Discriminative Models to Evaluate Generative Ones. - Timothée Lesort; Andrei Stoian; Jean-François Goudou; David Filliat (ICANN (3), 2019)

Generative Models from the perspective of Continual Learning. - Timothée Lesort; Hugo Caselles-Dupré; Michaël Garcia Ortiz; Andrei Stoian; David Filliat (IJCNN, 2019)

Deep unsupervised state representation learning with robotic priors: a robustness analysis. - Timothée Lesort; Mathieu Seurin; Xinrui Li; Natalia Díaz Rodríguez; David Filliat (IJCNN, 2019)

Decoupling feature extraction from policy learning: assessing benefits of state representation learning in goal based robotics. - Antonin Raffin; Ashley Hill; Kalifou René Traoré; Timothée Lesort; Natalia Díaz Rodríguez; David Filliat (CoRR, 2019)

Continual Reinforcement Learning deployed in Real-life using Policy Distillation and Sim2Real Transfer. - René Traoré; Hugo Caselles-Dupré; Timothée Lesort; Te Sun; Natalia Díaz Rodríguez; David Filliat (CoRR, 2019)

Continual Learning for Robotics. - Timothée Lesort; Vincenzo Lomonaco; Andrei Stoian; Davide Maltoni; David Filliat; Natalia Díaz Rodríguez (CoRR, 2019)

DisCoRL: Continual Reinforcement Learning via Policy Distillation. - René Traoré; Hugo Caselles-Dupré; Timothée Lesort; Te Sun; Guanghang Cai; Natalia Díaz Rodríguez; David Filliat (CoRR, 2019)

Regularization Shortcomings for Continual Learning. - Timothée Lesort; Andrei Stoian; David Filliat (CoRR, 2019)

Exploring to learn visual saliency: The RL-IAC approach. - Céline Craye; Timothée Lesort; David Filliat; Jean-François Goudou (Robotics Auton. Syst., 2019)

Continual Learning: Tackling Catastrophic Forgetting in Deep Neural Networks with Replay Processes. - Timothée Lesort (CoRR, 2020)

Continual learning for robotics: Definition, framework, learning strategies, opportunities and challenges. - Timothée Lesort; Vincenzo Lomonaco; Andrei Stoian; Davide Maltoni; David Filliat; Natalia Díaz Rodríguez (Inf. Fusion, 2020)

Apprentissage continu : S'attaquer à l'oubli foudroyant des réseaux de neurones profonds grâce aux méthodes à rejeu de données. (Continual Learning : Tackling Catastrophic Forgetting in Deep Neural Networks with Replay Processes). - Timothée Lesort (2020)

Continuum: Simple Management of Complex Continual Learning Scenarios. - Arthur Douillard; Timothée Lesort (CoRR, 2021)

Understanding Continual Learning Settings with Data Distribution Drift Analysis. - Timothée Lesort; Massimo Caccia; Irina Rish (CoRR, 2021)

Continual Learning in Deep Networks: an Analysis of the Last Layer. - Timothée Lesort; Thomas George; Irina Rish (CoRR, 2021)

Sequoia: A Software Framework to Unify Continual Learning Research. - 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; et al. (CoRR, 2021)

Continual Learning with Foundation Models: An Empirical Study of Latent Replay. - Oleksiy Ostapenko; Timothée Lesort; Pau Rodríguez; Md Rifat Arefin; Arthur Douillard; Irina Rish; Laurent Charlin (CoLLAs, 2022)

Tutorial - Continual Learning beyond classification. - Alexander Gepperth; Timothée Lesort (ESANN, 2022)

Continual Feature Selection: Spurious Features in Continual Learning. - Timothée Lesort (CoRR, 2022)

Foundational Models for Continual Learning: An Empirical Study of Latent Replay. - Oleksiy Ostapenko; Timothée Lesort; Pau Rodríguez; Md Rifat Arefin; Arthur Douillard; Irina Rish; Laurent Charlin (CoRR, 2022)

Scaling the Number of Tasks in Continual Learning. - Timothée Lesort; Oleksiy Ostapenko; Diganta Misra; Md Rifat Arefin; Pau Rodríguez; Laurent Charlin; Irina Rish (CoRR, 2022)

Beyond Supervised Continual Learning: a Review. - Benedikt Bagus; Alexander Gepperth; Timothée Lesort (CoRR, 2022)

Spurious Features in Continual Learning. - Timothée Lesort (AAAI Bridge Program, 2023)

Challenging Common Assumptions about Catastrophic Forgetting and Knowledge Accumulation. - Timothée Lesort; Oleksiy Ostapenko; Pau Rodríguez; Diganta Misra; Md Rifat Arefin; Laurent Charlin; Irina Rish (CoLLAs, 2023)

Continual Pre-Training of Large Language Models: How to (re)warm your model? - Kshitij Gupta; Benjamin Thérien; Adam Ibrahim; Mats L. Richter; Quentin Anthony; Eugene Belilovsky; Irina Rish; Timothée Lesort (CoRR, 2023)

A Study of Continual Learning Under Language Shift. - Evangelia Gogoulou; Timothée Lesort; Magnus Boman; Joakim Nivre (CoRR, 2023)

Continual Learning of Deep Neural Networks in The Age of Big Data. - Alexander Gepperth; Timothée Lesort (ESANN, 2024)

Continual Learning Under Language Shift. - Evangelia Gogoulou; Timothée Lesort; Magnus Boman; Joakim Nivre (TSD (1), 2024)

Simple and Scalable Strategies to Continually Pre-train Large Language Models. - Adam Ibrahim; Benjamin Thérien; Kshitij Gupta; Mats L. Richter; Quentin Gregory Anthony; Eugene Belilovsky; Timothée Lesort; Irina Rish (Trans. Mach. Learn. Res., 2024)

Amplifying pathological detection in EEG signaling pathways through cross-dataset transfer learning. - Mohammad-Javad Darvishi Bayazi; Mohammad Sajjad Ghaemi; Timothée Lesort; Md Rifat Arefin; Jocelyn Faubert; Irina Rish (Comput. Biol. Medicine, 2024)

Atlas: A Novel Pathology Foundation Model by Mayo Clinic, Charité, and Aignostics. - Maximilian Alber; Stephan Tietz; Jonas Dippel; Timo Milbich; Timothée Lesort; Panos Korfiatis; Moritz Krügener; Beatriz Perez Cancer; Neelay Shah; Alexander Möllers; Philipp Seegerer; Alexandra Carpen-Amarie; et al. (CoRR, 2025)