Lei Feng

Artificial Intelligence · with An · 2020–2022

A researcher in the Science corpus: 2 papers; trusts 158 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 53 citations into it
• Computer Vision and Pattern Recognition — 44 citations into it
• Representation & Self-Supervised Learning — 10 citations into it

Whom Lei Feng trusts overall

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

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

Who trusts Lei Feng overall

1. Chris Dongjoo Kim

Papers from Lei Feng's perspective

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

Their papers

• Mitigating Neural Network Overconfidence with Logit Normalization (2022) — 414 citations
• Combating Noisy Labels by Agreement: A Joint Training Method with Co-Regularization (2020) — 687 citations