Shizhao Sun

Artificial Intelligence · 2015–2016

A researcher in the Science corpus: 3 papers; trusts 142 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 50 citations into it
• Computer Vision and Pattern Recognition — 46 citations into it
• Model Architectures — 24 citations into it
• Optimization & Training — 13 citations into it
• Signal Processing — 11 citations into it
• Statistical Learning Theory — 8 citations into it
• Representation & Self-Supervised Learning — 7 citations into it
• Scaling & Learning Theory — 6 citations into it

Whom Shizhao Sun trusts overall

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

1. Geoffrey E. Hinton
2. Alex Krizhevsky
3. Yoshua Bengio
4. Peter L. Bartlett
5. Yann LeCun
6. L. Eon Bottou
7. Jimmy Ba
8. Christian Szegedy
9. Kaiming He
10. Ilya Sutskever

Who trusts Shizhao Sun overall

1. Taiji Suzuki
2. Hiroshi Abe

Papers from Shizhao Sun's perspective

Ordered by how strongly the researchers Shizhao Sun 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. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Large Margin Deep Neural Networks: Theory and Algorithms (2015) — 22 citations
• Ensemble-Compression: A New Method for Parallel Training of Deep Neural Networks (2016) — 30 citations
• On the Depth of Deep Neural Networks: A Theoretical View (2015) — 176 citations