Jun Zhu

Electrical and Electronic Engineering · with Deng · 2017–2018

A researcher in the Science corpus: 2 papers; trusts 4 researchers and is trusted by 9 researchers here, as inferred from the citation graph.

Subfields

• Electrical and Electronic Engineering — 35 citations into it; #4,358 of 16,539 by trust here, #7,640 by citations
• Cognitive Neuroscience — 29 citations into it; #3,581 of 10,852 by trust here, #4,616 by citations
• Cellular and Molecular Neuroscience — 15 citations into it
• Model Architectures — 9 citations into it
• Optimization & Training — 7 citations into it

Whom Jun Zhu trusts overall

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

1. Yoshua Bengio
2. Paul J. Werbos
3. Yann LeCun
4. Kaiming He

Who trusts Jun Zhu overall

1. Wei Fang
2. Man Yao
3. Shi-Wee Deng

Papers from Jun Zhu's perspective

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

1. Gradient-based learning applied to document recognition
2. Long Short-Term Memory
3. ImageNet classification with deep convolutional neural networks
4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
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. Going deeper with convolutions
9. ImageNet Large Scale Visual Recognition Challenge
10. ImageNet: A large-scale hierarchical image database

Their papers

• Spatio-Temporal Backpropagation for Training High-Performance Spiking Neural Networks (2017) — 1,368 citations
• Direct Training for Spiking Neural Networks: Faster, Larger, Better (2018) — 797 citations