๐Additional Material
Additional material you can freely explore!
Popular Continual Learning Reviews and Surveys
Continual Learning for Robotics: Definition, Framework, Learning Strategies, Opportunities and Challenges by Timothรฉe Lesort, Vincenzo Lomonaco, Andrei Stoian, Davide Maltoni, David Filliat and Natalia Dรญaz-Rodr\วตuez. Information Fusion, 52--68, 2020.
Continual Lifelong Learning with Neural Networks: A Review by German I Parisi, Ronald Kemker, Jose L Part, Christopher Kanan and Stefan Wermter. Neural Networks, 54--71, 2019.
A Continual Learning Survey: Defying Forgetting in Classification Tasks by Matthias De Lange, Rahaf Aljundi, Marc Masana, Sarah Parisot, Xu Jia, Ales Leonardis, Gregory Slabaugh and Tinne Tuytelaars. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021.
Additional papers
Never-Ending Learning by Tom Mitchell, William W Cohen, E Hruschka, Partha P Talukdar, B Yang, Justin Betteridge, Andrew Carlson, B Dalvi, Matt Gardner, Bryan Kisiel, J Krishnamurthy, Ni Lao, K Mazaitis, T Mohamed, N Nakashole, E Platanios, A Ritter, M Samadi, B Settles, R Wang, D Wijaya, A Gupta, X Chen, A Saparov, M Greaves and J Welling. Communications of the Acm, 2302--2310, 2015.
The ART of Adaptive Pattern Recognition by a Self-Organizing Neural Network by Gail A. Carpenter and Stephen Grossberg. Computer, 77--88, 1988.
CHILD: A First Step Towards Continual Learning by and Mark B Ring. Machine Learning, 77--104, 1997.
Useful Links about Resources on Continual learning
ContinualAI association main website
explore the ContinualAI projects and people
YouTube account of ContinualAI with many videos and seminars on continual learning
ContinualAI wiki, general resources on continual learning
research venues, industry players, software, tutorials and more
Continual Learning Papers on GitHub
you can see an organized list of continual learning papers
Continual Learning Papers with a dynamic and easy-to-use interface to navigate papers, aligned with GitHub resource above
Related Courses
"Continual Learning: Towards Broad AI": Advanced, seminar-style course at MILA, 2021.
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