Guy Boudoukh

Computer Vision and Pattern Recognition · 2017–2019

A researcher in the Science corpus: 2 papers; trusts 6 researchers and is trusted by 16 researchers here, as inferred from the citation graph.

Subfields

Whom Guy Boudoukh trusts overall

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

  1. Yoshua Bengio
  2. Karen Simonyan
  3. Andrew Zisserman
  4. Song Han
  5. Jacob Devlin
  6. Geoffrey E. Hinton
  7. Vincent Vanhoucke
  8. Alex Krizhevsky
  9. Diederik P. Kingma
  10. Yann LeCun

Who trusts Guy Boudoukh overall

  1. Sehoon Kim
  2. J. Scott McCarley
  3. Lu Hou
  4. Olga Kovaleva
  5. Anna Rogers
  6. Xinyin Ma
  7. Young Jin Kim
  8. Ali Hadi Zadeh
  9. Yuhui Li
  10. Canwen Xu

Papers from Guy Boudoukh's perspective

Ordered by how strongly the researchers Guy Boudoukh 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. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  4. Long Short-Term Memory
  5. Attention is All you Need (Neural Information Processing Systems)
  6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  7. Gradient-based learning applied to document recognition
  8. ImageNet: A large-scale hierarchical image database
  9. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
  10. Learning Multiple Layers of Features from Tiny Images

Their papers