Kun Yi

Artificial Intelligence · 2019

A researcher in the Science corpus: 1 paper; trusts 103 researchers and is trusted by 15 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 19 citations into it; #10,609 of 35,345 by trust here, #21,878 by citations
• Computer Vision and Pattern Recognition — 17 citations into it; #7,235 of 21,575 by trust here, #14,478 by citations
• Optimization & Training — 6 citations into it

Whom Kun Yi trusts overall

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

1. Alex Krizhevsky
2. Kaiming He
3. Arash Vahdat
4. X. Zhang
5. Geoffrey E. Hinton
6. Shaoqing Ren
7. Zhilu Zhang
8. Ross B. Girshick
9. Yann LeCun
10. Yoshua Bengio

Who trusts Kun Yi overall

1. Görkem Algan
2. Junnan Li
3. Haiyang Zhang
4. Yassine Ouali
5. Mamshad Nayeem Rizve
6. Shoaib Ahmed Siddiqui
7. Ilkay Ulusoy
8. Collin Burns
9. Richard Socher
10. Ximing Xing

Papers from Kun Yi's perspective

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

Their papers

• Probabilistic End-To-End Noise Correction for Learning With Noisy Labels (2019) — 488 citations