Continual Unsupervised Learning
Continual Unsupervised Learning is a machine learning paradigm that enables a model to incrementally acquire and retain knowledge from a continuous stream of unlabeled data while mitigating catastrophic forgetting, thereby distinguishing it from both traditional unsupervised learning and disjoint batch-based unsupervised learning approaches.
27
Publications
936
Citations
117
Authors
49
Institutions
Publications per year
2017–2026
25
Parents
27
Toward an artificial intelligence physicist for unsupervised learning
Tailin Wu, Max Tegmark · Physical review. E · 2019 · 103 citations · Full text
Computing, Computer Science, Physics +13
Continual Unsupervised Representation Learning
Dushyant Rao, Francesco Visin, Andrei Rusu et al. · arXiv (Cornell University) · 2019 · 86 citations · Full text
1–5 of 27
117
3
h-index
3
h-index
3
h-index
2
h-index
1
h-index
1–5 of 117
49
Rochester Institute of Technology
Rochester, United States
4 h-index
14 publications
229 citations
KU Leuven
Leuven, Belgium
3 h-index
6 publications
187 citations

Chinese Academy of Sciences
Beijing, China
1 h-index
5 publications
500 citations
University of Chinese Academy of Sciences
Beijing, China
1 h-index
2 publications
200 citations

Sorbonne Université
Paris, France
1 h-index
3 publications
54 citations

Xidian University
Xi'an, China
1 h-index
4 publications
124 citations

Centre National de la Recherche Scientifique
Paris, France
1 h-index
2 publications
42 citations

National University of Defense Technology
Changsha, China
1 h-index
4 publications
56 citations
1–8 of 49
Repository · 3 publications · 129 citations
3
h-index
Conference · 2 publications · 44 citations
2
h-index
Conference · 2 publications · 34 citations
2
h-index
1 publications · 26 citations
1
h-index
1 publications · 17 citations
1
h-index
1–5