Huijun Wu

Artificial Intelligence · 2017–2019

A researcher in the Science corpus: 2 papers; trusts 5 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 30 citations into it
• Safety, Robustness & Interpretability — 19 citations into it
• Computer Vision and Pattern Recognition — 11 citations into it
• Graph Learning — 9 citations into it

Whom Huijun Wu trusts overall

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

1. Olcay Boz
2. Matthew D. Zeiler
3. Geoffrey E. Hinton
4. Alex Krizhevsky
5. Thomas Kipf
6. Yann LeCun
7. Mark W. Craven
8. Ming Liang
9. Yoshua Bengio
10. Lada A. Adamic

Who trusts Huijun Wu overall

1. Marinka Zitnik
2. Wei Jin
3. Lichao Sun

Papers from Huijun Wu's perspective

Ordered by how strongly the researchers Huijun Wu 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. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. Going deeper with convolutions
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Adversarial Examples on Graph Data: Deep Insights into Attack and Defense (2019) — 514 citations
• Interpreting Shared Deep Learning Models via Explicable Boundary Trees (2017) — 6 citations