Richard Mao

Computer Vision and Pattern Recognition · 2021

A researcher in the Science corpus: 1 paper; trusts 31 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 49 citations into it
• Artificial Intelligence — 46 citations into it

Whom Richard Mao trusts overall

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

1. Kaiming He
2. Geoffrey E. Hinton
3. Alex Krizhevsky
4. Ross B. Girshick
5. Yoshua Bengio

Papers from Richard Mao's perspective

Ordered by how strongly the researchers Richard Mao 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 Large Scale Visual Recognition Challenge
3. ImageNet classification with deep convolutional neural networks
4. Gradient-based learning applied to document recognition
5. ImageNet: A large-scale hierarchical image database
6. Attention is All you Need (Neural Information Processing Systems)
7. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
8. Long Short-Term Memory
9. Going deeper with convolutions
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Self-Supervised Pretraining Improves Self-Supervised Pretraining (2021) — 137 citations