Neil C. Thompson

Artificial Intelligence · with Greenewald · 2020

A researcher in the Science corpus: 1 paper; trusts 248 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 64 citations into it
• Computer Vision and Pattern Recognition — 58 citations into it
• Scaling & Learning Theory — 13 citations into it
• Efficiency & Compression — 12 citations into it
• Model Architectures — 9 citations into it
• Representation & Self-Supervised Learning — 6 citations into it

Whom Neil C. Thompson trusts overall

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

1. Alex Krizhevsky
2. Geoffrey E. Hinton
3. Kaiming He
4. David G. Lowe
5. Yoshua Bengio
6. Ilya Sutskever
7. Yann LeCun
8. Diederik P. Kingma
9. Ross B. Girshick
10. Sepp Hochreiter

Who trusts Neil C. Thompson overall

1. Yaron Lipman
2. Sara Hooker
3. Ricky T. Q. Chen

Papers from Neil C. Thompson's perspective

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

Their papers

• The Computational Limits of Deep Learning (2020) — 707 citations