Hao Yang

Artificial Intelligence · with Gou · 2019–2020

A researcher in the Science corpus: 2 papers; trusts 52 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 40 citations into it
• Computer Vision and Pattern Recognition — 24 citations into it
• Graph Learning — 9 citations into it
• Safety, Robustness & Interpretability — 9 citations into it
• Representation & Self-Supervised Learning — 8 citations into it
• Model Architectures — 7 citations into it
• Molecular Biology — 5 citations into it

Whom Hao Yang trusts overall

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

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

Papers from Hao Yang's perspective

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

Their papers

• DySAT: Deep Neural Representation Learning on Dynamic Graphs via Self-Attention Networks (2020) — 771 citations
• DeepVID: Deep Visual Interpretation and Diagnosis for Image Classifiers via Knowledge Distillation (2019) — 120 citations