Liming Zhu

Artificial Intelligence · with Lu · 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 Liming Zhu trusts

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

1. Olcay Boz (in Artificial Intelligence)
2. Stephan Günnemann (in Graph Learning)
3. Rob Fergus (in Computer Vision and Pattern Recognition)
4. Matthew D. Zeiler (in Computer Vision and Pattern Recognition)
5. Max Welling (in Artificial Intelligence)

Papers from Liming Zhu's perspective

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

1. Explaining and Harnessing Adversarial Examples
2. Visualizing and Understanding Convolutional Networks
3. ImageNet classification with deep convolutional neural networks
4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
5. Deep Neural Networks for Acoustic Modeling in Speech Recognition: The Shared Views of Four Research Groups
6. Semi-Supervised Classification with Graph Convolutional Networks (International Conference on Learning Representations)
7. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
8. Gradient-based learning applied to document recognition
9. Learning Multiple Layers of Features from Tiny Images
10. Attention is All you Need (Neural Information Processing Systems)

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