Amir Najafi

Artificial Intelligence · 2018–2019

A researcher in the Science corpus: 2 papers; trusts 16 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

Whom Amir Najafi trusts overall

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

  1. Alex Krizhevsky
  2. Dong-Hyun Lee
  3. Marco Loog
  4. Yoshua Bengio
  5. Geoffrey E. Hinton
  6. Yves Grandvalet
  7. Massih-Reza Amini
  8. Christian Szegedy
  9. Yann LeCun
  10. Sergey Ioffe

Who trusts Amir Najafi overall

  1. Aditi Raghunathan
  2. Ananya Kumar
  3. Percy Liang
  4. Sang Michael Xie
  5. Sven Gowal
  6. Sylvestre-Alvise Rebuffi
  7. Tengyu Ma
  8. Da-Wei Zhou

Papers from Amir Najafi's perspective

Ordered by how strongly the researchers Amir Najafi 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  6. Long Short-Term Memory
  7. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  8. Attention is All you Need (Neural Information Processing Systems)
  9. ImageNet: A large-scale hierarchical image database
  10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers