Hongxin Wei

Artificial Intelligence · 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 Hongxin Wei trusts overall

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

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

Who trusts Hongxin Wei overall

1. Chris Dongjoo Kim
2. Jinseo Jeong

Papers from Hongxin Wei's perspective

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