Hanxun Huang

Artificial Intelligence · 2020

A researcher in the Science corpus: 1 paper; trusts 32 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 24 citations into it
• Computer Vision and Pattern Recognition — 19 citations into it

Whom Hanxun Huang trusts overall

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

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

Papers from Hanxun Huang's perspective

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

Their papers

• Normalized Loss Functions for Deep Learning with Noisy Labels (2020) — 563 citations