Russell Stewart

Artificial Intelligence · 2015–2020

A researcher in the Science corpus: 4 papers; trusts 250 researchers and is trusted by 269 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 47 citations into it; #5,613 of 35,345 by trust here, #6,569 by citations
• Computer Vision and Pattern Recognition — 43 citations into it; #2,430 of 21,575 by trust here, #5,236 by citations
• Representation & Self-Supervised Learning — 9 citations into it; #2,255 of 3,145 by trust here, #2,042 by citations
• Evaluation & Benchmarks — 7 citations into it
• Signal Processing — 7 citations into it
• Natural Language Processing — 6 citations into it
• Optimization & Training — 6 citations into it
• Statistical Learning Theory — 5 citations into it

Whom Russell Stewart trusts overall

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

1. Diederik P. Kingma
2. Ilya Sutskever
3. Christian Szegedy
4. Geoffrey E. Hinton
5. Alex Krizhevsky
6. Kaiming He
7. Yoshua Bengio
8. Ross B. Girshick
9. Yann LeCun
10. Jimmy Ba

Who trusts Russell Stewart overall

1. Yan Zhang
2. Xinlei Chen
3. Xiaodan Liang
4. Jan Hendrik Hosang
5. Ishan Misra
6. Jun Shu
7. Bernt Schiele
8. Jie Lei
9. Bingbing Ni
10. Andrea Vedaldi

Papers from Russell Stewart's perspective

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

Their papers

• End-to-End People Detection in Crowded Scenes (2015) — 586 citations
• Label-Free Supervision of Neural Networks with Physics and Domain Knowledge (2016) — 362 citations
• A Theory of Usable Information Under Computational Constraints (2020) — 217 citations
• Deep-learning-assisted diagnosis for knee magnetic resonance imaging: Development and retrospective validation of MRNet (2018) — 702 citations