Long Jin

Computer Vision and Pattern Recognition · with Lazarow · 2017

A researcher in the Science corpus: 2 papers; trusts 296 researchers and is trusted by 16 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 40 citations into it; #5,744 of 21,575 by trust here, #10,500 by citations
• Artificial Intelligence — 26 citations into it
• Generative Models — 22 citations into it; #782 of 1,956 by trust here, #1,502 by citations
• Probabilistic & Bayesian Methods — 17 citations into it
• Model Architectures — 11 citations into it
• Optimization & Training — 9 citations into it
• Signal Processing — 5 citations into it

Whom Long Jin 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. Yann LeCun
6. Yoshua Bengio
7. Zhuowen Tu
8. Ilya Sutskever
9. Christian Szegedy
10. Max Welling

Who trusts Long Jin overall

1. Jianwen Xie
2. Ruiqi Gao
3. Erik Nijkamp
4. Song-Chun Zhu
5. Ying Nian Wu
6. Kwonjoon Lee
7. Yang Lu
8. Weijian Xu
9. Yan Zhang
10. Diederik P. Kingma

Papers from Long Jin's perspective

Ordered by how strongly the researchers Long Jin 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Gradient-based learning applied to document recognition
5. Attention is All you Need (Neural Information Processing Systems)
6. Long Short-Term Memory
7. ImageNet: A large-scale hierarchical image database
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

• Introspective Classification with Convolutional Nets (2017) — 62 citations
• Introspective Neural Networks for Generative Modeling (2017) — 68 citations