Jinghui Chen

Artificial Intelligence · 1 papers · 2020

A researcher in the Science corpus: 1 paper; trusts 10 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 59 citations into it
• Safety, Robustness & Interpretability — 50 citations into it
• Computer Vision and Pattern Recognition — 18 citations into it
• Molecular Biology — 8 citations into it
• Electrical and Electronic Engineering — 7 citations into it
• Optimization & Training — 6 citations into it

Whom Jinghui Chen trusts overall

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

1. Alex Krizhevsky
2. Francesco Croce
3. Geoffrey E. Hinton
4. Kaiming He
5. Yoshua Bengio
6. Ian J. Goodfellow
7. Christian Szegedy
8. Diederik P. Kingma
9. Yann LeCun
10. Matthias Hein

Papers from Jinghui Chen's perspective

Ordered by how strongly the researchers Jinghui Chen 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. Learning Multiple Layers of Features from Tiny Images
4. Gradient-based learning applied to document recognition
5. ImageNet: A large-scale hierarchical image database
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. Long Short-Term Memory
8. Attention is All you Need (Neural Information Processing Systems)
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Do Wider Neural Networks Really Help Adversarial Robustness? (2020) — 106 citations