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ORCIDGido M. van de Ven
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- affiliation: KU Leuven, Belgium
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2020 – today
- 2024
[i13]Gido M. van de Ven, Nicholas Soures, Dhireesha Kudithipudi:
Continual Learning and Catastrophic Forgetting. CoRR abs/2403.05175 (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, Gido M. van de Ven:
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, Bing Liu, Vincenzo Lomonaco, Gido van de Ven, Andrea Cossu:
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
, Josh C. Bongard, Andrew P. Brna, Suraj Chakravarthi Raja, Nick Cheney, Jeff Clune, Anurag Reddy Daram, Stefano Fusi, Peter Helfer, Leslie Kay, Nicholas Ketz, Zsolt Kira, Soheil Kolouri, Jeffrey L. Krichmar, Sam Kriegman, Michael Levin, Sandeep Madireddy, Santosh Manicka, Ali Marjaninejad, Bruce McNaughton, Risto Miikkulainen, Zaneta Navratilova, Tej Pandit, Alice Parker, Praveen K. Pilly, Sebastian Risi, Terrence J. Sejnowski, Andrea Soltoggio, Nicholas Soures, Andreas S. Tolias, Darío Urbina-Meléndez, Francisco J. Valero Cuevas, Gido M. van de Ven, Joshua T. Vogelstein, Felix Wang, Ron Weiss, Angel Yanguas-Gil, Xinyun Zou, Hava T. Siegelmann:
Biological underpinnings for lifelong learning machines. Nat. Mach. Intell. 4(3): 196-210 (2022) - [j1]Gido M. van de Ven, Tinne Tuytelaars, Andreas S. Tolias:
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, 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, Jeremy Forest, Eden Belouadah, Simone Calderara, German Ignacio Parisi, Fabio Cuzzolin, Andreas S. Tolias, Simone Scardapane, Luca Antiga, Subutai Ahmad, Adrian Popescu, Christopher Kanan, Joost van de Weijer, Tinne Tuytelaars, Davide Bacciu, Davide Maltoni:
Avalanche: An End-to-End Library for Continual Learning. CVPR Workshops 2021: 3600-3610 - [c2]Gido M. van de Ven, Zhe Li, Andreas S. Tolias:
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, Jeremy Forest, Eden Belouadah, Simone Calderara, German Ignacio Parisi, Fabio Cuzzolin, Andreas S. Tolias, Simone Scardapane, Luca Antiga, Subutai Amhad, Adrian Popescu, Christopher Kanan, Joost van de Weijer, Tinne Tuytelaars, Davide Bacciu, Davide Maltoni:
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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