Continual learning: A comparative study on how to defy forgetting in classification tasks. - Matthias De Lange; Rahaf Aljundi; Marc Masana; Sarah Parisot; Xu Jia 012; Ales Leonardis; Gregory G. Slabaugh; Tinne Tuytelaars (CoRR, 2019)

Unsupervised Model Personalization While Preserving Privacy and Scalability: An Open Problem. - Matthias De Lange; Xu Jia 012; Sarah Parisot; Ales Leonardis; Gregory G. Slabaugh; Tinne Tuytelaars (CVPR, 2020)

Avalanche: An End-to-End Library for Continual Learning. - Vincenzo Lomonaco; Lorenzo Pellegrini; Andrea Cossu; Antonio Carta; Gabriele Graffieti; Tyler L. Hayes; Matthias De Lange; Marc Masana; Jary Pomponi; Gido M. van de Ven; Martin Mundt; Qi She; et al. (CVPR Workshops, 2021)

Continual Prototype Evolution: Learning Online from Non-Stationary Data Streams. - Matthias De Lange; Tinne Tuytelaars (ICCV, 2021)

Rehearsal revealed: The limits and merits of revisiting samples in continual learning. - Eli Verwimp; Matthias De Lange; Tinne Tuytelaars (ICCV, 2021)

Avalanche: an End-to-End Library for Continual Learning. - Vincenzo Lomonaco; Lorenzo Pellegrini; Andrea Cossu; Antonio Carta; Gabriele Graffieti; Tyler L. Hayes; Matthias De Lange; Marc Masana; Jary Pomponi; Gido M. van de Ven; Martin Mundt; Qi She; et al. (CoRR, 2021)

Re-examining Distillation for Continual Object Detection. - Eli Verwimp; Kuo Yang; Sarah Parisot; Lanqing Hong; Steven McDonagh 001; Eduardo Pérez-Pellitero; Matthias De Lange; Tinne Tuytelaars (BMVC, 2022)

3rd Continual Learning Workshop Challenge on Egocentric Category and Instance Level Object Understanding. - Lorenzo Pellegrini; Chenchen Zhu; Fanyi Xiao; Zhicheng Yan 001; Antonio Carta; Matthias De Lange; Vincenzo Lomonaco; Roshan Sumbaly; Pau Rodríguez; David Vázquez 001 (CoRR, 2022)

A Continual Learning Survey: Defying Forgetting in Classification Tasks. - Matthias De Lange; Rahaf Aljundi; Marc Masana; Sarah Parisot; Xu Jia 012; Ales Leonardis; Gregory G. Slabaugh; Tinne Tuytelaars (IEEE Trans. Pattern Anal. Mach. Intell., 2022)

Continual evaluation for lifelong learning: Identifying the stability gap. - Matthias De Lange; Gido M. van de Ven; Tinne Tuytelaars (ICLR, 2023)

EgoAdapt: A multi-stream evaluation study of adaptation to real-world egocentric user video. - Matthias De Lange; Hamid Eghbalzadeh; Reuben Tan; Michael L. Iuzzolino; Franziska Meier; Karl Ridgeway (CoRR, 2023)

Multiscale Video Pretraining for Long-Term Activity Forecasting. - Reuben Tan; Matthias De Lange; Michael L. Iuzzolino; Bryan A. Plummer; Kate Saenko; Karl Ridgeway; Lorenzo Torresani (CoRR, 2023)

CLAD: A realistic Continual Learning benchmark for Autonomous Driving. - Eli Verwimp; Kuo Yang; Sarah Parisot; Lanqing Hong; Steven McDonagh 001; Eduardo Pérez-Pellitero; Matthias De Lange; Tinne Tuytelaars (Neural Networks, 2023)

Towards Open-World Gesture Recognition. - Junxiao Shen; Matthias De Lange; Xuhai Xu; Enmin Zhou; Ran Tan; Naveen Suda; Maciej Lazarewicz; Per Ola Kristensson; Amy Karlson; Evan Strasnick (ISMAR, 2024)

Multilingual JobBERT for Cross-Lingual Job Title Matching. - Jens-Joris Decorte; Matthias De Lange; Jeroen Van Hautte (CoRR, 2025)