Yonggang Hu

Artificial Intelligence · 2019

A researcher in the Science corpus: 1 paper; trusts 28 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 17 citations into it
• Computer Vision and Pattern Recognition — 17 citations into it
• Model Architectures — 9 citations into it
• Optimization & Training — 9 citations into it

Whom Yonggang Hu trusts overall

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

1. Alex Krizhevsky
2. Geoffrey E. Hinton
3. Yoshua Bengio
4. James Bergstra
5. Hugo Larochelle
6. Kaiming He
7. Yann LeCun
8. Barret Zoph
9. Christian Szegedy

Papers from Yonggang Hu's perspective

Ordered by how strongly the researchers Yonggang Hu trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Learning Multiple Layers of Features from Tiny Images
4. Going deeper with convolutions
5. Gradient-based learning applied to document recognition
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. Long Short-Term Memory
8. Attention is All you Need (Neural Information Processing Systems)
9. ImageNet: A large-scale hierarchical image database
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Transferable AutoML by Model Sharing Over Grouped Datasets (2019) — 24 citations