Prototypical Learning
Prototypical Learning is a metric learning approach that learns class-specific prototypes in an embedding space, where each prototype serves as a representative summary of feature vectors for a given class, enabling classification through nearest-prototype distance comparison.
202
Publications
16.4K
Citations
619
Authors
258
Institutions
Publications per year
2017–2026
151
Parents
202
Prototypical Networks for Few-shot Learning
Jake Snell, Kevin Swersky, Richard S. Zemel · arXiv (Cornell University) · 2017 · 5.2K citations · Full text
Meta-Learning for Semi-Supervised Few-Shot Classification
Mengye Ren, Eleni Triantafillou, Sachin Ravi et al. · arXiv (Cornell University) · 2018 · 728 citations · Full text
Prototypical Contrastive Learning of Unsupervised Representations
Junnan Li, Pan Zhou, Caiming Xiong et al. · arXiv (Cornell University) · 2020 · 484 citations · Full text
Transferrable Prototypical Networks for Unsupervised Domain Adaptation
Yingwei Pan, Ting Yao, Yehao Li et al. · 2019 · 398 citations
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258
Google (United States)
Mountain View, United States
7 h-index
14 publications
724 citations

Chinese Academy of Sciences
Beijing, China
6 h-index
20 publications
803 citations

City University of Hong Kong
Hong Kong, Hong Kong
5 h-index
8 publications
776 citations
University of Chinese Academy of Sciences
Beijing, China
5 h-index
11 publications
531 citations

University of Toronto
Toronto, Canada
5 h-index
9 publications
894 citations
Massachusetts Institute of Technology
Cambridge, United States
5 h-index
12 publications
1.5K citations
University of Southern California
Los Angeles, United States
4 h-index
7 publications
181 citations

Northwestern Polytechnical University
Xi'an, China
4 h-index
13 publications
930 citations
1–8 of 258
Repository · 32 publications · 7.4K citations
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Conference · 6 publications · 377 citations
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Conference · 5 publications · 369 citations
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5 publications · 212 citations
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4 publications · 93 citations
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