Contrastive Learning
Contrastive Learning is a self-supervised learning framework that learns meaningful representations by attracting similar (positive) pairs and repelling dissimilar (negative) pairs in the embedding space.
2.8K
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240.2K
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10.5K
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1.4K
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Publications per year
2017–2026
2.7K
2.8K
A Fast Learning Algorithm for Deep Belief Nets
Geoffrey E. Hinton, Simon Osindero, Yee‐Whye Teh · Neural Computation · 2006 · 16.4K citations
Momentum Contrast for Unsupervised Visual Representation Learning
Kaiming He, Haoqi Fan, Yuxin Wu et al. · 2020 · 12K citations
A Simple Framework for Contrastive Learning of Visual Representations
Ting Chen, Simon Kornblith, Mohammad Norouzi et al. · arXiv (Cornell University) · 2020 · 7.3K citations · Full text
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Tsinghua University
Beijing, China
45 h-index
278 publications
24.4K citations

Peking University
Beijing, China
43 h-index
277 publications
36.1K citations

Chinese Academy of Sciences
Beijing, China
41 h-index
269 publications
16.7K citations
Nanyang Technological University
Singapore, Singapore
39 h-index
180 publications
13.3K citations

Zhejiang University
Hangzhou, China
38 h-index
221 publications
12.2K citations
University of Science and Technology of China
Hefei, China
37 h-index
191 publications
9.4K citations
Tencent (China)
Shenzhen, China
37 h-index
203 publications
18.7K citations

Harbin Institute of Technology
Harbin, China
36 h-index
173 publications
9.3K citations
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Repository · 502 publications · 49.9K citations
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Conference · 124 publications · 8.8K citations
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Conference · 94 publications · 7.7K citations
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81 publications · 4.4K citations
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Conference · 61 publications · 6.3K citations
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