Matthias De Lange
Matthias De Lange
PhD researcher @ KU Leuven
Verified email at - Homepage
Cited by
Cited by
A continual learning survey: Defying forgetting in classification tasks
M De Lange, R Aljundi, M Masana, S Parisot, X Jia, A Leonardis, ...
TPAMI, 2021
Avalanche: an end-to-end library for continual learning
V Lomonaco, L Pellegrini, A Cossu, A Carta, G Graffieti, TL Hayes, ...
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021
Continual prototype evolution: Learning online from non-stationary data streams
M De Lange, T Tuytelaars
ICCV 2021, 2020
Rehearsal revealed: The limits and merits of revisiting samples in continual learning
E Verwimp*, M De Lange*, T Tuytelaars
ICCV 2021, 2021
Unsupervised Model Personalization while Preserving Privacy and Scalability: An Open Problem
M De Lange, X Jia, S Parisot, A Leonardis, G Slabaugh, T Tuytelaars
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020
Re-examining distillation for continual object detection
E Verwimp, K Yang, S Parisot, H Lanqing, S McDonagh, E Pérez-Pellitero, ...
arXiv preprint arXiv:2204.01407, 2022
Continual evaluation for lifelong learning: Identifying the stability gap
M De Lange, G van de Ven, T Tuytelaars
International Conference on Learning Representations (ICLR), 2023
CLAD: A realistic Continual Learning benchmark for Autonomous Driving
E Verwimp, K Yang, S Parisot, L Hong, S McDonagh, E Pérez-Pellitero, ...
Neural Networks 161, 659-669, 2023
Incremental and adaptive machine learning.
M De Lange, T Tuytelaars
3rd Continual Learning Workshop Challenge on Egocentric Category and Instance Level Object Understanding
L Pellegrini, C Zhu, F Xiao, Z Yan, A Carta, M De Lange, V Lomonaco, ...
arXiv preprint arXiv:2212.06833, 2022
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