Yurong You

Computer Vision and Pattern Recognition · 2017–2019

A researcher in the Science corpus: 3 papers; trusts 197 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 72 citations into it; #13,088 of 21,575 by trust here, #7,421 by citations
• Artificial Intelligence — 55 citations into it; #21,033 of 35,345 by trust here, #12,974 by citations
• Safety, Robustness & Interpretability — 29 citations into it
• Aerospace Engineering — 27 citations into it
• Reinforcement Learning — 21 citations into it
• Computational Mechanics — 7 citations into it
• Model Architectures — 7 citations into it
• Robotics & Control — 6 citations into it

Whom Yurong You trusts overall

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

1. Kaiming He
2. Geoffrey E. Hinton
3. Alex Krizhevsky
4. Ross B. Girshick
5. Yoshua Bengio
6. Diederik P. Kingma
7. Yann LeCun
8. Christian Szegedy
9. Ilya Sutskever
10. Karen Simonyan

Who trusts Yurong You overall

1. Shansi Zhang
2. Jack Stilgoe
3. Douwe van der Wal
4. Wilko Schwarting
5. Jonah Philion
6. Jie M. Zhang
7. Michal Uřičář
8. Victor Talpaert
9. Wenyuan Zeng
10. Pranav Singh Chib

Papers from Yurong You's perspective

Ordered by how strongly the researchers Yurong You 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. ImageNet: A large-scale hierarchical image database
5. Gradient-based learning applied to document recognition
6. Long Short-Term Memory
7. Attention is All you Need (Neural Information Processing Systems)
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• Virtual to Real Reinforcement Learning for Autonomous Driving (2017) — 356 citations
• Pseudo-LiDAR++: Accurate Depth for 3D Object Detection in Autonomous Driving (2019) — 446 citations
• Simple Black-box Adversarial Attacks (2019) — 714 citations