Ryan J. Gallagher

Artificial Intelligence · 2016

A researcher in the Science corpus: 1 paper; trusts 7 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

Whom Ryan J. Gallagher trusts overall

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

  1. T. Landauer
  2. Sanjeev Arora
  3. David M. Blei
  4. Radim Rehurek
  5. Matthew D. Hoffman
  6. David Andrzejewski
  7. Jagadeesh Jagarlamudi
  8. Rong Ge
  9. T. Griffiths
  10. Jonathan D. Chang

Who trusts Ryan J. Gallagher overall

  1. Shuyang Gao
  2. Daniel Moyer
  3. Roman Egger
  4. Rob Brekelmans
  5. Greg Ver Steeg
  6. Joanne Yu
  7. Aram Galstyan

Papers from Ryan J. Gallagher's perspective

Ordered by how strongly the researchers Ryan J. Gallagher 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. Gradient-based learning applied to document recognition
  5. ImageNet: A large-scale hierarchical image database
  6. Learning Multiple Layers of Features from Tiny Images
  7. Attention is All you Need (Neural Information Processing Systems)
  8. Long Short-Term Memory
  9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers