Kun Zhan

Computer Vision and Pattern Recognition · 2018–2019

A researcher in the Science corpus: 2 papers; trusts 24 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 33 citations into it
• Artificial Intelligence — 18 citations into it
• Representation & Self-Supervised Learning — 8 citations into it
• Statistical and Nonlinear Physics — 6 citations into it

Whom Kun Zhan trusts overall

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

1. Feiping Nie
2. Ulrike von Luxburg
3. Sham M. Kakade
4. Andrew Y. Ng
5. René Vidal
6. Michael I. Jordan
7. Jianbo Shi
8. Abhishek Kumar
9. Changqing Zhang
10. Arthur Gretton

Who trusts Kun Zhan overall

1. Jie Xu
2. Feiping Nie

Papers from Kun Zhan's perspective

Ordered by how strongly the researchers Kun Zhan 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Gradient-based learning applied to document recognition
5. ImageNet: A large-scale hierarchical image database
6. Attention is All you Need (Neural Information Processing Systems)
7. Long Short-Term Memory
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Learning Multiple Layers of Features from Tiny Images
10. Going deeper with convolutions

Their papers

• Multiview Consensus Graph Clustering (2019) — 484 citations
• Graph Learning for Multiview Clustering (2018) — 429 citations