Zhenyu Guo

Artificial Intelligence · with Wang · 2013–2018

A researcher in the Science corpus: 2 papers; trusts 240 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 31 citations into it
• Computer Vision and Pattern Recognition — 30 citations into it
• Optimization & Training — 17 citations into it
• Representation & Self-Supervised Learning — 12 citations into it
• Statistical Learning Theory — 6 citations into it

Whom Zhenyu Guo trusts overall

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

1. David G. Lowe
2. John Blitzer
3. Hal Daumé Iii
4. Lixin Duan
5. Christopher Evans
6. Navneet Dalal
7. Brian Kulis
8. Geoffrey E. Hinton
9. Aude Oliva
10. Kate Saenko

Papers from Zhenyu Guo's perspective

Ordered by how strongly the researchers Zhenyu Guo 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. Gradient-based learning applied to document recognition
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. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Highly Scalable Deep Learning Training System with Mixed-Precision: Training ImageNet in Four Minutes (2018) — 423 citations
• Cross-Domain Object Recognition Via Input-Output Kernel Analysis (2013) — 43 citations