William J. Christmas

Computer Vision and Pattern Recognition · 2015

A researcher in the Science corpus: 1 paper; trusts 82 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom William J. Christmas trusts overall

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

  1. Yi Sun
  2. Karen Simonyan
  3. Alex Krizhevsky
  4. Geoffrey E. Hinton
  5. Andrew Zisserman
  6. Kaiming He
  7. Andrea Vedaldi
  8. Christian Szegedy
  9. Ilya Sutskever

Papers from William J. Christmas's perspective

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

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

Their papers