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Continual learning is the problem of learning from a nonstationary stream of data, a fundamental issue for sustainable and efficient training of deep neural networks over time.
Progressive Neural Networks
Andrei A. Rusu, Neil C. Rabinowitz, Guillaume Desjardins, Hubert Soyer, James Kirkpatrick, Koray Kavukcuoglu, Razvan Pascanu, and Raia Hadsell · 2016
Earlier work this paper cites.
Continual learning for robotics: Definition, framework, learning strategies, opportunities and challenges
Timothée Lesort, Vincenzo Lomonaco, Andrei Stoian, Davide Maltoni, David Filliat, and Natalia Díaz-Rodríguez · 2019
Earlier work this paper cites.
PyTorch: An Imperative Style, High-Performance Deep Learning Library
Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, Alban Desmaison, Andreas Kopf, Edward Yang, Zachary DeVito, Martin Raison, Alykhan Tejani, Sasank Chilamkurthy, Benoit Steiner, Lu Fang, Junjie Bai, and Soumith Chintala · 2019
Earlier work this paper cites.
Continuum: Simple Management of Complex Continual Learning Scenarios
Arthur Douillard and Timothée Lesort · 2021
Cited alongside, same era.
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, Keiland Cooper, Jeremy Forest, Eden Belouadah, Simone Calderara, German I. Parisi, Fabio Cuzzolin, Andreas S. Tolias, Simone Scardapane, Luca Antiga, Subutai Ahmad, Adrian Popescu, Christopher Kanan, Joost van de Weijer, Tinne Tuytelaars, Davide Bacciu, and Davide Maltoni · 2021
Cited alongside, same era.
CL-Gym: Full-Featured PyTorch Library for Continual Learning
Seyed Iman Mirzadeh and Hassan Ghasemzadeh · 2021
Cited alongside, same era.
Continual World: A Robotic Benchmark For Continual Reinforcement Learning
Maciej Wolczyk, Michał Zajkac, Razvan Pascanu, Łukasz Kuciński, and Piotr Miłoś · 2021
Later among the works it cites.
Class-Incremental Learning: Survey and Performance Evaluation on Image Classification
Marc Masana, Xialei Liu, Bartłomiej Twardowski, Mikel Menta, Andrew D. Bagdanov, and Joost van de Weijer · 2022
Later among the works it cites.
Sequoia: A Software Framework to Unify Continual Learning Research, January 2022
Fabrice Normandin, Florian Golemo, Oleksiy Ostapenko, Pau Rodriguez, Matthew D. Riemer, Julio Hurtado, Khimya Khetarpal, Ryan Lindeborg, Lucas Cecchi, Timothée Lesort, Laurent Charlin, Irina Rish, and Massimo Caccia · 2022
Later among the works it cites.
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