Phil Barber

Artificial Intelligence · 2015–2019

A researcher in the Science corpus: 2 papers; trusts 47 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

Whom Phil Barber trusts overall

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

  1. Yann LeCun
  2. Geoffrey E. Hinton
  3. Yoshua Bengio
  4. Diederik P. Kingma
  5. L. Eon Bottou
  6. Alex Krizhevsky
  7. Richard S. Sutton
  8. Andrew Y. Ng
  9. Ilya Sutskever
  10. J. Urgen Schmidhuber

Who trusts Phil Barber overall

  1. Ling Xu

Papers from Phil Barber's perspective

Ordered by how strongly the researchers Phil Barber 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. Gradient-based learning applied to document recognition
  5. Long Short-Term Memory
  6. Attention is All you Need (Neural Information Processing Systems)
  7. ImageNet: A large-scale hierarchical image database
  8. Learning Multiple Layers of Features from Tiny Images
  9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  10. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)

Their papers