Philip N. Garner

Artificial Intelligence · 2011–2021

A researcher in the Science corpus: 9 papers; trusts 60 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

Whom Philip N. Garner trusts overall

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

  1. Geoffrey E. Hinton
  2. Diederik P. Kingma
  3. Yoshua Bengio
  4. Dong Yu
  5. Jimmy Ba
  6. Heiga Zen
  7. Alan W. Black
  8. Alex Krizhevsky
  9. Mark John Francis Gales
  10. Daniel Povey

Who trusts Philip N. Garner overall

  1. Srihari Kankanahalli
  2. Pawel Swietojanski
  3. Andreas Triantafyllopoulos

Papers from Philip N. Garner's perspective

Ordered by how strongly the researchers Philip N. Garner 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. 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. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
  9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers