Kun Yan

Computer Vision and Pattern Recognition · with Wang · 2019–2021

A researcher in the Science corpus: 2 papers; trusts 279 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 80 citations into it
• Artificial Intelligence — 76 citations into it
• Efficiency & Compression — 23 citations into it
• Representation & Self-Supervised Learning — 20 citations into it
• Model Architectures — 17 citations into it
• Optimization & Training — 9 citations into it
• Media Technology — 5 citations into it

Whom Kun Yan trusts overall

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

1. Alex Krizhevsky
2. Kaiming He
3. Geoffrey E. Hinton
4. Ilya Sutskever
5. Karen Simonyan
6. Sergey Ioffe
7. Yoshua Bengio
8. Christian Szegedy
9. Ross B. Girshick
10. Yann LeCun

Who trusts Kun Yan overall

1. Yang He
2. Charles Herrmann

Papers from Kun Yan's perspective

Ordered by how strongly the researchers Kun Yan 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. ImageNet: A large-scale hierarchical image database
5. Attention is All you Need (Neural Information Processing Systems)
6. Long Short-Term Memory
7. Gradient-based learning applied to document recognition
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

• Gate Decorator: Global Filter Pruning Method for Accelerating Deep Convolutional Neural Networks (2019) — 295 citations
• Aligning Visual Prototypes with BERT Embeddings for Few-Shot Learning (2021) — 36 citations