Michael Rudzsky

Computer Vision and Pattern Recognition · 2009

A researcher in the Science corpus: 1 paper; trusts 59 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Michael Rudzsky trusts overall

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

  1. Frederick Jelinek
  2. Andrew McCallum
  3. Charles Sutton
  4. John D. Lafferty
  5. Yuri A. Ivanov
  6. Fengjun Lv
  7. Shu-Fai Wong
  8. Ramkant Nevatia
  9. Geoffrey E. Hinton
  10. Sebastian Nowozin

Papers from Michael Rudzsky's perspective

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

  1. ImageNet classification with deep convolutional neural networks
  2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  4. Gradient-based learning applied to document recognition
  5. Long Short-Term Memory
  6. ImageNet: A large-scale hierarchical image database
  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. Going deeper with convolutions
  10. ImageNet Large Scale Visual Recognition Challenge

Their papers