Paul Rayson

Artificial Intelligence · 2000–2020

A researcher in the Science corpus: 4 papers; trusts 13 researchers and is trusted by 20 researchers here, as inferred from the citation graph.

Subfields

Whom Paul Rayson trusts overall

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

  1. N. Schmitt
  2. Alex Graves
  3. J. Urgen Schmidhuber
  4. Sepp Hochreiter
  5. Tomas Mikolov
  6. Douglas Biber
  7. Yequan Wang
  8. Maria Pontiki
  9. Ivan A. Sag
  10. Geoffrey E. Hinton

Who trusts Paul Rayson overall

  1. Caroline Tagg
  2. Andrew Hardie
  3. Serge Sharoff
  4. Rose Hendricks
  5. Richard Xiao
  6. Emiel van Miltenburg
  7. Akshay Java
  8. Zsófia Demjén
  9. Hongyin Tao
  10. Desmond Elliott

Papers from Paul Rayson's perspective

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

  1. Long Short-Term Memory
  2. ImageNet classification with deep convolutional neural networks
  3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  4. Gradient-based learning applied to document recognition
  5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  6. Attention is All you Need (Neural Information Processing Systems)
  7. Efficient Estimation of Word Representations in Vector Space
  8. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
  9. Learning Multiple Layers of Features from Tiny Images
  10. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)

Their papers