Siyuan Shan

Computer Vision and Pattern Recognition · 2017–2019

A researcher in the Science corpus: 2 papers; trusts 260 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 51 citations into it; #20,290 of 21,575 by trust here, #20,756 by citations
• Artificial Intelligence — 29 citations into it; #33,161 of 35,345 by trust here, #33,294 by citations
• Representation & Self-Supervised Learning — 17 citations into it
• Model Architectures — 9 citations into it
• Optimization & Training — 5 citations into it

Whom Siyuan Shan trusts overall

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

1. Alex Krizhevsky
2. Diederik P. Kingma
3. Geoffrey E. Hinton
4. Kaiming He
5. Yann LeCun
6. Yoshua Bengio
7. Karen Simonyan
8. Alex Graves
9. Jimmy Ba
10. Ilya Sutskever

Who trusts Siyuan Shan overall

1. Arvid Lundervold
2. Marvin Zhang
3. Henrik Marklund

Papers from Siyuan Shan's perspective

Ordered by how strongly the researchers Siyuan Shan 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. Long Short-Term Memory
7. Attention is All you Need (Neural Information Processing Systems)
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

• Meta-Neighborhoods (2019) — 17 citations
• Unsupervised End-to-end Learning for Deformable Medical Image Registration (2017) — 55 citations