Nicholas Cain

Artificial Intelligence · 2014–2020

A researcher in the Science corpus: 2 papers; trusts 34 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 20 citations into it
• Computer Vision and Pattern Recognition — 15 citations into it
• Probabilistic & Bayesian Methods — 5 citations into it

Whom Nicholas Cain trusts overall

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

1. Kaiming He
2. Bianca Zadrozny
3. Alex Krizhevsky
4. Yann LeCun
5. Gao Huang
6. J. Platt
7. Geoffrey E. Hinton
8. John K. Kruschke
9. Jochen Bröcker
10. Yoshua Bengio

Who trusts Nicholas Cain overall

1. Raphael Gontijo Lopes

Papers from Nicholas Cain's perspective

Ordered by how strongly the researchers Nicholas Cain 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. Gradient-based learning applied to document recognition
4. ImageNet: A large-scale hierarchical image database
5. Learning Multiple Layers of Features from Tiny Images
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. Attention is All you Need (Neural Information Processing Systems)
8. Long Short-Term Memory
9. Going deeper with convolutions
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Mitigating bias in calibration error estimation (2020) — 131 citations
• A mesoscale connectome of the mouse brain (2014) — 2,461 citations