Zhengyang Wang

Computer Vision and Pattern Recognition · with Ji · 2018

A researcher in the Science corpus: 2 papers; trusts 476 researchers and is trusted by 10 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 43 citations into it
• Artificial Intelligence — 32 citations into it; #14,401 of 35,345 by trust here, #13,353 by citations
• Model Architectures — 18 citations into it
• Graph Learning — 12 citations into it
• Molecular Biology — 7 citations into it; #4,894 of 17,773 by trust here, #9,030 by citations
• Natural Language Processing — 7 citations into it
• Optimization & Training — 7 citations into it
• Representation & Self-Supervised Learning — 6 citations into it

Whom Zhengyang Wang trusts overall

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

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

Who trusts Zhengyang Wang overall

1. Kaixiong Zhou
2. Dongdong Chen
3. Hongyang Gao
4. Shuiwang Ji
5. Fan Zhou
6. Hao Yuan
7. Huan Zhao
8. Yao Ma
9. Si Zhang
10. Mingming He

Papers from Zhengyang Wang's perspective

Ordered by how strongly the researchers Zhengyang Wang 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. Gradient-based learning applied to document recognition
5. Attention is All you Need (Neural Information Processing Systems)
6. Long Short-Term Memory
7. ImageNet: A large-scale hierarchical image database
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Going deeper with convolutions
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Smoothed dilated convolutions for improved dense prediction (2018) — 188 citations
• Large-Scale Learnable Graph Convolutional Networks (2018) — 656 citations