Shuai Li

Artificial Intelligence · with Barbastathis · 2014–2019

A researcher in the Science corpus: 5 papers; trusts 293 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 84 citations into it; #27,593 of 35,345 by trust here, #15,866 by citations
• Computer Vision and Pattern Recognition — 82 citations into it; #18,911 of 21,575 by trust here, #9,435 by citations
• Model Architectures — 52 citations into it
• Optimization & Training — 30 citations into it
• Computational Mechanics — 11 citations into it; #8,809 of 10,001 by trust here, #8,566 by citations
• Statistical Learning Theory — 11 citations into it
• Natural Language Processing — 11 citations into it
• Atomic and Molecular Physics, and Optics — 10 citations into it

Whom Shuai Li trusts overall

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

1. Alex Krizhevsky
2. Geoffrey E. Hinton
3. Yoshua Bengio
4. Kaiming He
5. Diederik P. Kingma
6. Yann LeCun
7. Ilya Sutskever
8. Karen Simonyan
9. Ross B. Girshick
10. Sepp Hochreiter

Who trusts Shuai Li overall

1. Hui Tang
2. Meng Lyu
3. Yunzhe Li
4. Lei Shi
5. Mostafa Karimi
6. Lei Huang
7. Anirudh Goyal
8. Yifan Zhang
9. K. Jia
10. Kamyar Azizzadenesheli

Papers from Shuai Li's perspective

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

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

Their papers

• Independently Recurrent Neural Network (IndRNN): Building A Longer and Deeper RNN (2018) — 824 citations
• Online Clustering of Bandits (2014) — 289 citations
• Imaging through glass diffusers using densely connected convolutional networks (2017) — 345 citations
• Orthogonal Deep Neural Networks (2019) — 164 citations
• Lensless computational imaging through deep learning (2017) — 588 citations