J.-L. Chu

Computer Vision and Pattern Recognition · 2022

A researcher in the Science corpus: 1 paper; trusts 159 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 35 citations into it; #13,480 of 21,575 by trust here, #18,782 by citations
• Artificial Intelligence — 30 citations into it; #21,778 of 35,345 by trust here, #29,412 by citations
• Natural Language Processing — 9 citations into it
• Evaluation & Benchmarks — 5 citations into it

Whom J.-L. Chu trusts overall

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

1. Kaiming He
2. Geoffrey E. Hinton
3. Alex Krizhevsky
4. Diederik P. Kingma
5. Yoshua Bengio
6. Ross B. Girshick
7. Ilya Sutskever
8. Yann LeCun
9. Andrew Zisserman
10. Karen Simonyan

Who trusts J.-L. Chu overall

1. Yabin Wang
2. Sarah Pratt
3. Jingyi Zhang

Papers from J.-L. Chu's perspective

Ordered by how strongly the researchers J.-L. Chu 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. Attention is All you Need (Neural Information Processing Systems)
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. ImageNet: A large-scale hierarchical image database
6. Gradient-based learning applied to document recognition
7. Long Short-Term Memory
8. ImageNet Large Scale Visual Recognition Challenge
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Going deeper with convolutions

Their papers

• Unsupervised Prompt Learning for Vision-Language Models (2022) — 182 citations