Tristan Cook

Artificial Intelligence · 2019

A researcher in the Science corpus: 1 paper; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Tristan Cook trusts overall

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

  1. Scott Aaronson

Papers from Tristan Cook's perspective

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

  1. GradientBased Learning Applied to Document Recognition
  2. Unsupervised Learning of Invariant Feature Hierarchies with Applications to Object Recognition
  3. Read the fine print (Nature Physics)
  4. Gradient-based learning applied to document recognition
  5. ImageNet classification with deep convolutional neural networks
  6. Distinctive Image Features from Scale-Invariant Keypoints
  7. Attention is All you Need (Neural Information Processing Systems)
  8. Long Short-Term Memory
  9. Training Products of Experts by Minimizing Contrastive Divergence
  10. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)

Their papers