Jingwei Zhao

Artificial Intelligence · with Chen · 2020–2021

A researcher in the Science corpus: 2 papers; trusts 33 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 67 citations into it
• Optimization & Training — 36 citations into it
• Computer Vision and Pattern Recognition — 34 citations into it
• Safety, Robustness & Interpretability — 13 citations into it
• Civil and Structural Engineering — 10 citations into it
• Representation & Self-Supervised Learning — 9 citations into it

Whom Jingwei Zhao trusts overall

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

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

Papers from Jingwei Zhao's perspective

Ordered by how strongly the researchers Jingwei Zhao 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. Learning Multiple Layers of Features from Tiny Images
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Gradient-based learning applied to document recognition
6. ImageNet: A large-scale hierarchical image database
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

• Noise against noise: stochastic label noise helps combat inherent label noise (2021) — 46 citations
• Beyond Class-Conditional Assumption: A Primary Attempt to Combat Instance-Dependent Label Noise (2020) — 159 citations