Yao Hu

Artificial Intelligence · with Fang · 2019

A researcher in the Science corpus: 1 paper; trusts 5 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 14 citations into it
• Computer Vision and Pattern Recognition — 14 citations into it

Whom Yao Hu trusts overall

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

1. Geoffrey E. Hinton
2. Diederik P. Kingma
3. Kaiming He
4. Thomas G. Dietterich

Papers from Yao Hu's perspective

Ordered by how strongly the researchers Yao 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
3. ImageNet classification with deep convolutional neural networks
4. Dropout: a simple way to prevent neural networks from overfitting
5. Distilling the Knowledge in a Neural Network (arXiv.org)
6. Gradient-based learning applied to document recognition
7. Attention is All you Need (Neural Information Processing Systems)
8. Long Short-Term Memory
9. Learning Multiple Layers of Features from Tiny Images
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Knowledge Amalgamation from Heterogeneous Networks by Common Feature Learning (2019) — 59 citations