Lie Qu

Artificial Intelligence · 2019

A researcher in the Science corpus: 1 paper; trusts 4 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 16 citations into it; #31,161 of 35,345 by trust here, #29,412 by citations
• Computer Vision and Pattern Recognition — 11 citations into it; #19,183 of 21,575 by trust here, #18,782 by citations

Whom Lie Qu trusts overall

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

1. Alex Krizhevsky
2. Kaiming He
3. Oriol Vinyals
4. Geoffrey E. Hinton
5. Yoshua Bengio
6. X. Zhang
7. Yann LeCun
8. Shaoqing Ren
9. Diederik P. Kingma
10. Tong Xiao

Who trusts Lie Qu overall

1. Görkem Algan
2. Hwanjun Song

Papers from Lie Qu's perspective

Ordered by how strongly the researchers Lie Qu 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Long Short-Term Memory
7. ImageNet: A large-scale hierarchical image database
8. Attention is All you Need (Neural Information Processing Systems)
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• O2U-Net: A Simple Noisy Label Detection Approach for Deep Neural Networks (2019) — 283 citations