Zhilu Zhang

Artificial Intelligence · 2018–2020

A researcher in the Science corpus: 2 papers; trusts 304 researchers and is trusted by 61 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 60 citations into it; #4,430 of 35,345 by trust here, #9,760 by citations
• Computer Vision and Pattern Recognition — 39 citations into it; #14,963 of 21,575 by trust here, #21,103 by citations
• Optimization & Training — 16 citations into it; #508 of 2,601 by trust here, #930 by citations
• Efficiency & Compression — 14 citations into it
• Representation & Self-Supervised Learning — 9 citations into it
• Safety, Robustness & Interpretability — 9 citations into it; #308 of 2,251 by trust here, #876 by citations
• Evaluation & Benchmarks — 7 citations into it
• Model Architectures — 6 citations into it

Whom Zhilu Zhang trusts overall

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

1. Alex Krizhevsky
2. Geoffrey E. Hinton
3. Kaiming He
4. Diederik P. Kingma
5. Yoshua Bengio
6. Yann LeCun
7. Ilya Sutskever
8. X. Zhang
9. Jimmy Ba
10. Jia Deng

Who trusts Zhilu Zhang overall

1. Eduardo Fonseca
2. Xingjun Ma
3. Kun Yi
4. Xiaobo Xia
5. Yisen Wang
6. Pengfei Chen
7. Yixiao Ge
8. Wei Hu
9. Damien Dablain
10. Chris Dongjoo Kim

Papers from Zhilu Zhang's perspective

Ordered by how strongly the researchers Zhilu Zhang 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. Learning Multiple Layers of Features from Tiny Images
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Generalized Cross Entropy Loss for Training Deep Neural Networks with Noisy Labels (2018) — 3,268 citations
• Self-Distillation as Instance-Specific Label Smoothing (2020) — 151 citations