James Stokes

Artificial Intelligence · 2018–2019

A researcher in the Science corpus: 2 papers; trusts 33 researchers and is trusted by 20 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 23 citations into it; #7,821 of 35,345 by trust here, #13,962 by citations
• Generative Models — 14 citations into it; #582 of 1,956 by trust here, #1,382 by citations
• Optimization & Training — 12 citations into it
• Computer Vision and Pattern Recognition — 11 citations into it
• Statistical and Nonlinear Physics — 6 citations into it; #1,645 of 10,127 by trust here, #3,979 by citations

Whom James Stokes trusts overall

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

1. Maria Schuld
2. Diederik P. Kingma
3. James C. Spall
4. Edward Farhi
5. Jarrod R. McClean
6. Ville Bergholm
7. Individualized Treat
8. Jimmy Ba
9. Geoffrey E. Hinton
10. Kosuke Mitarai

Who trusts James Stokes overall

1. Waïss Azizian
2. M. Cerezo
3. Yu-Guan Hsieh
4. Lennart Bittel
5. Gauthier Gidel
6. David Wierichs
7. Josh A. Izaac
8. Ioannis Mitliagkas
9. Ville Bergholm
10. Aryan Mokhtari

Papers from James Stokes's perspective

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

Their papers

• Interaction Matters: A Note on Non-asymptotic Local Convergence of Generative Adversarial Networks (2018) — 226 citations
• Quantum Natural Gradient (2019) — 537 citations