Jun Zhao

Artificial Intelligence · with Han · 2019

A researcher in the Science corpus: 1 paper; trusts 19 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 — 23 citations into it
• Signal Processing — 19 citations into it
• Management Science and Operations Research — 16 citations into it
• Model Architectures — 15 citations into it
• Control and Systems Engineering — 8 citations into it
• Economics and Econometrics — 6 citations into it

Whom Jun Zhao trusts overall

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

1. Geoffrey E. Hinton
2. Yoshua Bengio
3. Yann LeCun
4. Alex Graves
5. Ilya Sutskever
6. J. Urgen Schmidhuber
7. Alex Krizhevsky
8. Diederik P. Kingma
9. Vladimir Naumovich Vapni
10. Sepp Hochreiter

Papers from Jun Zhao's perspective

Ordered by how strongly the researchers Jun Zhao trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Long Short-Term Memory
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Gradient-based learning applied to document recognition
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. GENERATIVE ADVERSARIAL NETS
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• A Review of Deep Learning Models for Time Series Prediction (2019) — 455 citations