Gabriel Deza

Artificial Intelligence · 2021

A researcher in the Science corpus: 1 paper; trusts 8 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Gabriel Deza trusts overall

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

  1. Alex Krizhevsky
  2. Karen Simonyan
  3. Kaiming He
  4. Geoffrey E. Hinton
  5. Liwei Song
  6. Andrew Zisserman
  7. X. Zhang
  8. Laura Graves
  9. Ilya Sutskever
  10. Yoshua Bengio

Papers from Gabriel Deza's perspective

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

Their papers