Qiqi Yan

Computer Vision and Pattern Recognition · 2010–2018

A researcher in the Science corpus: 5 papers; trusts 226 researchers and is trusted by 239 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 45 citations into it
• Artificial Intelligence — 41 citations into it; #1,367 of 35,345 by trust here, #2,401 by citations
• Safety, Robustness & Interpretability — 38 citations into it
• Natural Language Processing — 13 citations into it; #434 of 5,688 by trust here, #607 by citations
• Management Science and Operations Research — 10 citations into it; #9,130 of 11,946 by trust here, #11,360 by citations
• Model Architectures — 8 citations into it
• Biophysics — 6 citations into it
• Computer Networks and Communications — 6 citations into it; #3,329 of 9,886 by trust here, #7,492 by citations

Whom Qiqi Yan trusts overall

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

1. Yoshua Bengio
2. Geoffrey E. Hinton
3. Christian Szegedy
4. Ilya Sutskever
5. Karen Simonyan
6. Alex Krizhevsky
7. Aranyak Mehta
8. Matthew D. Zeiler
9. Yann LeCun
10. Diederik P. Kingma

Who trusts Qiqi Yan overall

1. Mukund Sundararajan
2. Aranyak Mehta
3. Wojciech Samek
4. Umang Bhatt
5. Laura Rieger
6. Marco Ancona
7. Been Kim
8. Xisen Jin
9. Scott M. Lundberg
10. Sara Hooker

Papers from Qiqi Yan's perspective

Ordered by how strongly the researchers Qiqi Yan 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. Gradient-based learning applied to document recognition
5. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet Large Scale Visual Recognition Challenge
8. Going deeper with convolutions
9. ImageNet: A large-scale hierarchical image database
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Axiomatic Attribution for Deep Networks (2017) — 8,293 citations
• How Important Is a Neuron? (2018) — 159 citations
• Online bipartite matching with random arrivals: an approach based on strongly factor-revealing LPs (2011) — 300 citations
• Revenue maximization with a single sample (2010) — 305 citations
• Gradients of Counterfactuals (2016) — 115 citations