Hao Cheng

Artificial Intelligence · with An · 2019–2022

A researcher in the Science corpus: 2 papers; trusts 107 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 70 citations into it
• Computer Vision and Pattern Recognition — 56 citations into it
• Representation & Self-Supervised Learning — 8 citations into it

Whom Hao Cheng trusts overall

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

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

Papers from Hao Cheng's perspective

Ordered by how strongly the researchers Hao Cheng 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
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
• Adversarial Robustness vs. Model Compression, or Both? (2019) — 181 citations