Ben Z. Yuan

Artificial Intelligence · 2018

A researcher in the Science corpus: 2 papers; trusts 134 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 91 citations into it
• Safety, Robustness & Interpretability — 73 citations into it
• Computer Vision and Pattern Recognition — 60 citations into it
• Biophysics — 12 citations into it
• Natural Language Processing — 12 citations into it
• Model Architectures — 10 citations into it
• Computational Theory and Mathematics — 8 citations into it

Whom Ben Z. Yuan trusts overall

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

1. Geoffrey E. Hinton
2. Kaiming He
3. Matthew D. Zeiler
4. Alex Krizhevsky
5. Diederik P. Kingma
6. Yoshua Bengio
7. Quanshi Zhang
8. Yann LeCun
9. Karen Simonyan
10. Bolei Zhou

Papers from Ben Z. Yuan's perspective

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

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

Their papers

• Explaining Explanations: An Overview of Interpretability of Machine Learning (2018) — 2,256 citations
• Explaining Explanations: An Approach to Evaluating Interpretability of Machine Learning (2018) — 187 citations