Kai Lu

Artificial Intelligence · with Wang · 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 Kai Lu trusts overall

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

1. Olcay Boz

Papers from Kai Lu's perspective

Ordered by how strongly the researchers Kai Lu 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. Explaining and Harnessing Adversarial Examples
4. Visualizing and Understanding Convolutional Networks
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Gradient-based learning applied to document recognition
7. Learning Multiple Layers of Features from Tiny Images
8. Attention is All you Need (Neural Information Processing Systems)
9. Long Short-Term Memory
10. ImageNet: A large-scale hierarchical image database

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