Paul Albert

Computer Vision and Pattern Recognition · 2019

A researcher in the Science corpus: 2 papers; trusts 160 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 56 citations into it; #19,919 of 21,575 by trust here, #7,938 by citations
• Artificial Intelligence — 49 citations into it; #32,293 of 35,345 by trust here, #11,327 by citations
• Representation & Self-Supervised Learning — 25 citations into it
• Optimization & Training — 17 citations into it

Whom Paul Albert trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Alex Krizhevsky
2. Kaiming He
3. Geoffrey E. Hinton
4. Yoshua Bengio
5. Diederik P. Kingma
6. Ilya Sutskever
7. Yann LeCun
8. Ross B. Girshick
9. Jia Deng
10. X. Zhang

Who trusts Paul Albert overall

1. Pengfei Chen
2. Junnan Li

Papers from Paul Albert's perspective

Ordered by how strongly the researchers Paul Albert trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. ImageNet: A large-scale hierarchical image database
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Gradient-based learning applied to document recognition
6. Learning Multiple Layers of Features from Tiny Images
7. Attention is All you Need (Neural Information Processing Systems)
8. Long Short-Term Memory
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Pseudo-Labeling and Confirmation Bias in Deep Semi-Supervised Learning (2019) — 1,104 citations
• Unsupervised label noise modeling and loss correction (2019) — 750 citations