Unsupervised Feature Learning is a machine learning approach that automatically discovers latent structures or patterns in unlabeled data by learning representative features without reliance on supervised annotations.
1.7K
Publications
169.8K
Citations
5.4K
Authors
1.6K
Institutions
Publications per year
2017–2026
1K
Parents
Publications
1.7K
Extracting and composing robust features with denoising autoencoders
Pascal Vincent, Hugo Larochelle, Yoshua Bengio et al. · 2008 · 7.3K citations
Reading digits in natural images with unsupervised feature learning
Yuval Netzer · 2024 · 4.6K citations · Full text
1–5 of 1.7K
Authors
5.4K
- FN
17
h-index
- YT
16
h-index
- XL
14
h-index
- LJ
13
h-index
- AY
12
h-index
1–5 of 5.4K
Institutions
1.6K
Chinese Academy of Sciences
Beijing, China
32 h-index
105 publications
7.8K citations
Tsinghua University
Beijing, China
28 h-index
103 publications
7.5K citations
Northwestern Polytechnical University
Xi'an, China
25 h-index
104 publications
6.1K citations
Nanyang Technological University
Singapore, Singapore
23 h-index
76 publications
6.3K citations
Xidian University
Xi'an, China
21 h-index
86 publications
8K citations
University of Chinese Academy of Sciences
Beijing, China
18 h-index
53 publications
1.7K citations
University of Electronic Science and Technology of China
Chengdu, China
18 h-index
40 publications
2.8K citations
Stanford University
Stanford, United States
18 h-index
55 publications
37.7K citations
1–8 of 1.6K
Venues
- arXiv (Cornell University)
Repository · 117 publications · 16.7K citations
40
h-index
- Neurocomputing
38 publications · 2K citations
26
h-index
- Pattern Recognition
30 publications · 2.3K citations
25
h-index
- Knowledge-Based Systems
25 publications · 1.2K citations
21
h-index
- IEEE Transactions on Geoscience and Remote Sensing
24 publications · 3.3K citations
21
h-index
1–5