Cade Gordon

Computer Vision and Pattern Recognition · 2022

A researcher in the Science corpus: 2 papers; trusts 62 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 112 citations into it; #20,896 of 21,575 by trust here, #3,035 by citations
• Artificial Intelligence — 90 citations into it; #34,378 of 35,345 by trust here, #3,998 by citations

Whom Cade Gordon trusts overall

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

1. Alex Krizhevsky
2. Diederik P. Kingma
3. Geoffrey E. Hinton
4. Kaiming He
5. Yoshua Bengio
6. Xiaohua Zhai
7. Yann LeCun
8. Ilya Sutskever
9. Jia Deng
10. Ross B. Girshick

Who trusts Cade Gordon overall

1. Ludwig Schmidt

Papers from Cade Gordon's perspective

Ordered by how strongly the researchers Cade Gordon 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. 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. ImageNet Large Scale Visual Recognition Challenge
7. Long Short-Term Memory
8. Gradient-based learning applied to document recognition
9. Microsoft COCO: Common Objects in Context
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• LAION-5B: An open large-scale dataset for training next generation image-text models (2022) — 5,389 citations
• Reproducible Scaling Laws for Contrastive Language-Image Learning (2022) — 1,494 citations