Ken Kansky

Computer Vision and Pattern Recognition · 2017

A researcher in the Science corpus: 2 papers; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Ken Kansky trusts overall

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

  1. Daphne Koller
  2. Carlos Guestrin
  3. Geoffrey E. Hinton
  4. Yann LeCun
  5. Yoshua Bengio
  6. Volodymyr Mnih
  7. Diederik P. Kingma
  8. Alex Krizhevsky
  9. Karen Simonyan
  10. David Silver

Who trusts Ken Kansky overall

  1. Sjoerd van Steenkiste
  2. Gary F. Marcus
  3. Vincent François-Lavet
  4. Melrose Roderick
  5. Klaus Greff
  6. Sam Toyer
  7. Charles Packer
  8. Honghua Dong
  9. Yuxi Li
  10. Adam Kortylewski

Papers from Ken Kansky's perspective

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

  1. ImageNet classification with deep convolutional neural networks
  2. Gradient-based learning applied to document recognition
  3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  4. ImageNet: A large-scale hierarchical image database
  5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  6. Long Short-Term Memory
  7. Attention is All you Need (Neural Information Processing Systems)
  8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  9. Learning Multiple Layers of Features from Tiny Images
  10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers