Yueru Chen

Computer Vision and Pattern Recognition · 2018–2019

A researcher in the Science corpus: 2 papers; trusts 21 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 37 citations into it
• Artificial Intelligence — 27 citations into it
• Safety, Robustness & Interpretability — 11 citations into it

Whom Yueru Chen trusts overall

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

1. C.-C. Jay Kuo
2. Alex Krizhevsky
3. Geoffrey E. Hinton
4. Ian J. Goodfellow
5. Diederik P. Kingma

Papers from Yueru Chen's perspective

Ordered by how strongly the researchers Yueru Chen 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. Gradient-based learning applied to document recognition
4. GENERATIVE ADVERSARIAL NETS
5. Dropout: a simple way to prevent neural networks from overfitting
6. Auto-Encoding Variational Bayes (International Conference on Learning Representations)
7. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
8. ImageNet: A large-scale hierarchical image database
9. Long Short-Term Memory
10. Attention is All you Need (Neural Information Processing Systems)

Their papers

• An Interpretable Generative Model for Handwritten Digits Synthesis (2019) — 4 citations
• Interpretable Convolutional Neural Networks via Feedforward Design (2018) — 177 citations