Xu Lan

Computer Vision and Pattern Recognition · 2018–2020

A researcher in the Science corpus: 3 papers; trusts 402 researchers and is trusted by 31 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 87 citations into it; #5,012 of 21,575 by trust here, #6,671 by citations
• Artificial Intelligence — 78 citations into it; #6,571 of 35,345 by trust here, #9,465 by citations
• Model Architectures — 20 citations into it
• Optimization & Training — 19 citations into it
• Representation & Self-Supervised Learning — 19 citations into it
• Efficiency & Compression — 17 citations into it; #255 of 1,264 by trust here, #644 by citations
• Signal Processing — 7 citations into it

Whom Xu Lan trusts overall

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

1. Alex Krizhevsky
2. Geoffrey E. Hinton
3. Kaiming He
4. Yoshua Bengio
5. Diederik P. Kingma
6. Jimmy Ba
7. Ross B. Girshick
8. Yann LeCun
9. Ilya Sutskever
10. Gao Huang

Who trusts Xu Lan overall

1. Seonguk Park
2. Hankook Lee
3. Jangho Kim
4. Lin Wang
5. Nojun Kwak
6. Jianping Gou
7. Feng Zhang
8. Anbang Yao
9. Zhilu Zhang
10. Jang Hyun Cho

Papers from Xu Lan's perspective

Ordered by how strongly the researchers Xu Lan 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Long Short-Term Memory
5. ImageNet: A large-scale hierarchical image database
6. Gradient-based learning applied to document recognition
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

• Knowledge Distillation by On-the-Fly Native Ensemble (2018) — 547 citations
• Boosting Few-Shot Learning With Adaptive Margin Loss (2020) — 224 citations
• Self-Referenced Deep Learning (2018) — 27 citations