Gang Xiong

Artificial Intelligence · with Liu · 2016

A researcher in the Science corpus: 2 papers; trusts 13 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 31 citations into it
• Computer Vision and Pattern Recognition — 25 citations into it
• Safety, Robustness & Interpretability — 22 citations into it
• Representation & Self-Supervised Learning — 11 citations into it

Whom Gang Xiong trusts overall

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

1. Geoffrey E. Hinton
2. Yann LeCun

Papers from Gang Xiong's perspective

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

1. Dropout: a simple way to prevent neural networks from overfitting
2. ImageNet classification with deep convolutional neural networks
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Intriguing properties of neural networks
5. Gradient-based learning applied to document recognition
6. Explaining and Harnessing Adversarial Examples
7. Visualizing and Understanding Convolutional Networks
8. Long Short-Term Memory
9. Learning Multiple Layers of Features from Tiny Images
10. Visualizing Data using t-SNE

Their papers

• Using Non-invertible Data Transformations to Build Adversary-Resistant Deep Neural Networks (2016) — 10 citations
• Using Non-invertible Data Transformations to Build Adversarial-Robust Neural Networks (2016) — 10 citations