Richard Strong Bowen

Artificial Intelligence · 2018–2020

A researcher in the Science corpus: 2 papers; trusts 341 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 72 citations into it
• Computer Vision and Pattern Recognition — 67 citations into it
• Efficiency & Compression — 44 citations into it
• Model Architectures — 24 citations into it; #2,190 of 2,278 by trust here, #2,215 by citations
• Optimization & Training — 8 citations into it; #1,767 of 2,601 by trust here, #2,484 by citations
• Generative Models — 6 citations into it

Whom Richard Strong Bowen trusts overall

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

1. Alex Graves
2. Yoshua Bengio
3. Geoffrey E. Hinton
4. Alex Krizhevsky
5. Kaiming He
6. Yann LeCun
7. Diederik P. Kingma
8. Ilya Sutskever
9. Song Han
10. Karen Simonyan

Who trusts Richard Strong Bowen overall

1. Yizeng Han
2. Gao Huang
3. Zhenda Xie

Papers from Richard Strong Bowen's perspective

Ordered by how strongly the researchers Richard Strong Bowen 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. ImageNet: A large-scale hierarchical image database
5. Gradient-based learning applied to document recognition
6. Long Short-Term Memory
7. Attention is All you Need (Neural Information Processing Systems)
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Going deeper with convolutions
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Channel Selection Using Gumbel Softmax (2020) — 64 citations
• An end-to-end approach for speeding up neural network inference (2018) — 5 citations