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

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)

Knowledge Accumulation in Continually Learned Representations and the Issue of Feature Forgetting. - Timm Hess; Eli Verwimp; Gido M. van de Ven; Tinne Tuytelaars (Trans. Mach. Learn. Res., 2024)

Continual Learning: Applications and the Road Forward. - Eli Verwimp; Rahaf Aljundi; Shai Ben-David; Matthias Bethge; Andrea Cossu; Alexander Gepperth; Tyler L. Hayes; Eyke Hüllermeier; Christopher Kanan; Dhireesha Kudithipudi; Christoph H. Lampert; Martin Mundt; et al. (Trans. Mach. Learn. Res., 2024)

Same accuracy, twice as fast: continuous training surpasses retraining from scratch. - Eli Verwimp; Guy Hacohen; Tinne Tuytelaars (CoRR, 2025)

Signs of the Past, Patterns of the Present: On the Automatic Classification of Old Babylonian Cuneiform Signs. - Eli Verwimp; Gustav Ryberg Smidt; Hendrik Hameeuw; Katrien de Graef (CoRR, 2025)