Yong Han

Artificial Intelligence · 2019

A researcher in the Science corpus: 1 paper; trusts 64 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 17 citations into it
• Safety, Robustness & Interpretability — 16 citations into it
• Computer Vision and Pattern Recognition — 15 citations into it
• Biophysics — 6 citations into it

Whom Yong Han trusts overall

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

1. Yann LeCun
2. Karen Simonyan
3. Geoffrey E. Hinton
4. Yoshua Bengio
5. Matthew D. Zeiler
6. Alex Krizhevsky
7. Individualized Treat
8. Been Kim
9. Kaiming He
10. Diederik P. Kingma

Papers from Yong Han's perspective

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

1. Gradient-based learning applied to document recognition
2. ImageNet classification with deep convolutional neural networks
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. GENERATIVE ADVERSARIAL NETS
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. Long Short-Term Memory
9. ImageNet Large Scale Visual Recognition Challenge
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Generative Counterfactual Introspection for Explainable Deep Learning (2019) — 97 citations