Nicholas Apostoloff

Computer Vision and Pattern Recognition · 2018

A researcher in the Science corpus: 1 paper; trusts 164 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Nicholas Apostoloff trusts overall

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

  1. Alex Krizhevsky
  2. Geoffrey E. Hinton
  3. Kaiming He
  4. Karen Simonyan
  5. Yann LeCun
  6. Yoshua Bengio
  7. Andrew Zisserman
  8. Song Han
  9. Diederik P. Kingma
  10. Jia Deng

Papers from Nicholas Apostoloff's perspective

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

Their papers