Albert Eaton Shaw

Artificial Intelligence · 2017–2020

A researcher in the Science corpus: 4 papers; trusts 319 researchers and is trusted by 9 researchers here, as inferred from the citation graph.

Subfields

Whom Albert Eaton Shaw trusts overall

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

  1. Richard S. Sutton
  2. Geoffrey E. Hinton
  3. E. Todorov
  4. Alex Krizhevsky
  5. Ronald J. Williams
  6. Kaiming He
  7. Yurii E. Nesterov
  8. John Schulman
  9. Yoshua Bengio
  10. Diederik P. Kingma

Who trusts Albert Eaton Shaw overall

  1. Ofir Nachum
  2. Bo Dai
  3. Ziyang Tang
  4. Lihong Li
  5. Yihao Feng
  6. Shangtong Zhang
  7. Donghwan Lee
  8. Niao He
  9. Nan Jiang
  10. Sergey Levine

Papers from Albert Eaton Shaw's perspective

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

  1. ImageNet classification with deep convolutional neural networks
  2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  4. Attention is All you Need (Neural Information Processing Systems)
  5. Long Short-Term Memory
  6. Gradient-based learning applied to document recognition
  7. ImageNet: A large-scale hierarchical image database
  8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  9. ImageNet Large Scale Visual Recognition Challenge
  10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers