Nathan Silberman

Computer Vision and Pattern Recognition · 2009–2016

A researcher in the Science corpus: 7 papers; trusts 801 researchers and is trusted by 6,250 researchers here, as inferred from the citation graph.

Subfields

Whom Nathan Silberman trusts overall

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

  1. Pablo Arbeláez
  2. Derek Hoiem
  3. Geoffrey E. Hinton
  4. Alex Krizhevsky
  5. Yann LeCun
  6. Ross B. Girshick
  7. Kaiming He
  8. Yoshua Bengio
  9. Alexei A. Efros
  10. Jitendra Malik

Who trusts Nathan Silberman overall

  1. Abhinav Kumar Gupta
  2. Shuran Song
  3. Saurabh Gupta
  4. Chunhua Shen
  5. X. Wang
  6. Jitendra Malik
  7. Luc Van Gool
  8. Ross B. Girshick
  9. Trevor Darrell
  10. Raquel Urtasun

Papers from Nathan Silberman's perspective

Ordered by how strongly the researchers Nathan Silberman 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. ImageNet: A large-scale hierarchical image database
  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. ImageNet Large Scale Visual Recognition Challenge
  10. Going deeper with convolutions

Their papers