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Gido M. van de Ven
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- affiliation: KU Leuven, Belgium
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2020 – today
- 2024
- [j4]Timm Hess, Eli Verwimp, Gido M. van de Ven, Tinne Tuytelaars:
Knowledge Accumulation in Continually Learned Representations and the Issue of Feature Forgetting. Trans. Mach. Learn. Res. 2024 (2024) - [j3]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, Razvan Pascanu, Adrian Popescu, Andreas S. Tolias, Joost van de Weijer, Bing Liu, Vincenzo Lomonaco, Tinne Tuytelaars, Gido M. van de Ven:
Continual Learning: Applications and the Road Forward. Trans. Mach. Learn. Res. 2024 (2024) - [c6]Michal Zajac, Tinne Tuytelaars, Gido M. van de Ven:
Prediction Error-based Classification for Class-Incremental Learning. ICLR 2024 - [i14]Gido M. van de Ven, Nicholas Soures, Dhireesha Kudithipudi:
Continual Learning and Catastrophic Forgetting. CoRR abs/2403.05175 (2024) - [i13]Hamed Hemati, Lorenzo Pellegrini, Xiaotian Duan, Zixuan Zhao, Fangfang Xia, Marc Masana, Benedikt Tscheschner, Eduardo Veas, Yuxiang Zheng, Shiji Zhao, Shao-Yuan Li, Sheng-Jun Huang, Vincenzo Lomonaco, Gido M. van de Ven:
Continual Learning in the Presence of Repetition. CoRR abs/2405.04101 (2024) - 2023
- [c5]Matthias De Lange, Gido M. van de Ven, Tinne Tuytelaars:
Continual evaluation for lifelong learning: Identifying the stability gap. ICLR 2023 - [i12]Timm Hess, Eli Verwimp, Gido M. van de Ven, Tinne Tuytelaars
:
Knowledge Accumulation in Continually Learned Representations and the Issue of Feature Forgetting. CoRR abs/2304.00933 (2023) - [i11]Michal Zajac, Tinne Tuytelaars, Gido M. van de Ven:
Prediction Error-based Classification for Class-Incremental Learning. CoRR abs/2305.18806 (2023) - [i10]Timm Hess, Tinne Tuytelaars, Gido M. van de Ven:
Two Complementary Perspectives to Continual Learning: Ask Not Only What to Optimize, But Also How. CoRR abs/2311.04898 (2023) - [i9]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, Razvan Pascanu, Adrian Popescu, Andreas S. Tolias, Joost van de Weijer, Bing Liu, Vincenzo Lomonaco, Tinne Tuytelaars, Gido M. van de Ven:
Continual Learning: Applications and the Road Forward. CoRR abs/2311.11908 (2023) - [i8]Sergi Masip, Pau Rodríguez, Tinne Tuytelaars
Continual Learning of Diffusion Models with Generative Distillation. CoRR abs/2311.14028 (2023) - [i7]Sebastian Dziadzio, Çagatay Yildiz, Gido M. van de Ven, Tomasz Trzcinski, Tinne Tuytelaars, Matthias Bethge:
Disentangled Continual Learning: Separating Memory Edits from Model Updates. CoRR abs/2312.16731 (2023) - [i6]Tinne Tuytelaars
Deep Continual Learning (Dagstuhl Seminar 23122). Dagstuhl Reports 13(3): 74-91 (2023) - 2022
- [j2]Dhireesha Kudithipudi, Mario Aguilar-Simon, Jonathan Babb, Maxim Bazhenov, Douglas Blackiston
Biological underpinnings for lifelong learning machines. Nat. Mach. Intell. 4(3): 196-210 (2022) - [j1]Gido M. van de Ven
Three types of incremental learning. Nat. Mac. Intell. 4(12): 1185-1197 (2022) - [c4]Shuang Li, Yilun Du, Gido van de Ven, Igor Mordatch:
Energy-Based Models for Continual Learning. CoLLAs 2022: 1-22 - [i5]Matthias De Lange, Gido van de Ven, Tinne Tuytelaars:
Continual evaluation for lifelong learning: Identifying the stability gap. CoRR abs/2205.13452 (2022) - 2021
- [c3]Vincenzo Lomonaco
Avalanche: An End-to-End Library for Continual Learning. CVPR Workshops 2021: 3600-3610 - [c2]Gido M. van de Ven
Class-Incremental Learning With Generative Classifiers. CVPR Workshops 2021: 3611-3620 - [c1]Ta-Chu Kao, Kristopher T. Jensen, Gido van de Ven, Alberto Bernacchia, Guillaume Hennequin:
Natural continual learning: success is a journey, not (just) a destination. NeurIPS 2021: 28067-28079 - [i4]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, Keiland W. Cooper
Avalanche: an End-to-End Library for Continual Learning. CoRR abs/2104.00405 (2021) - [i3]Gido M. van de Ven, Zhe Li, Andreas S. Tolias:
Class-Incremental Learning with Generative Classifiers. CoRR abs/2104.10093 (2021) - 2020
- [i2]Shuang Li, Yilun Du, Gido M. van de Ven, Antonio Torralba, Igor Mordatch:
Energy-Based Models for Continual Learning. CoRR abs/2011.12216 (2020)
2010 – 2019
- 2019
- [i1]Gido M. van de Ven, Andreas S. Tolias:
Three scenarios for continual learning. CoRR abs/1904.07734 (2019)
Coauthor Index
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