Evan Patterson

Artificial Intelligence · 2019

A researcher in the Science corpus: 1 paper; trusts 19 researchers and is trusted by 13 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 12 citations into it; #9,392 of 35,345 by trust here, #23,077 by citations
• Statistics and Probability — 9 citations into it; #3,234 of 12,932 by trust here, #6,310 by citations

Whom Evan Patterson trusts overall

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

1. Harris Papadopoulos
2. Jing Lei
3. Vladimir G Vovk
4. Nicolai Meinshausen
5. James W. Taylor
6. Diederik P. Kingma
7. Roger W. Koenker
8. Ingo Steinwart
9. David R. Hunter
10. Geoffrey E. Hinton

Who trusts Evan Patterson overall

1. E.J. Candes
2. Isaac Gibbs
3. Anastasios Nikolas Angelopoulos
4. Yaniv Romano
5. Leying Guan
6. Matteo Sesia
7. Lihua Lei
8. Maxime Cauchois
9. Stephen Bates
10. Rina Foygel Barber

Papers from Evan Patterson's perspective

Ordered by how strongly the researchers Evan Patterson trusts endorse each paper. Same corpus, a different order for every researcher.

1. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
2. ImageNet classification with deep convolutional neural networks
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Dropout: a simple way to prevent neural networks from overfitting
5. Gradient-based learning applied to document recognition
6. Attention is All you Need (Neural Information Processing Systems)
7. Long Short-Term Memory
8. ImageNet: A large-scale hierarchical image database
9. Learning Multiple Layers of Features from Tiny Images
10. Going deeper with convolutions

Their papers

• Conformalized Quantile Regression (2019) — 1,038 citations