Rachel Greenstadt

Artificial Intelligence · 2011–2014

A researcher in the Science corpus: 4 papers; trusts 42 researchers and is trusted by 12 researchers here, as inferred from the citation graph.

Subfields

Whom Rachel Greenstadt trusts overall

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

  1. David G. Lowe
  2. Christopher Evans
  3. Fabien A. P. Petitcolas
  4. Li Fei-Fei
  5. Krystian Mikolajczyk
  6. J. Ross Quinlan
  7. David M. Blei
  8. Josef Sivic
  9. Anthony Y. Fu
  10. Cordelia Schmid

Who trusts Rachel Greenstadt overall

  1. Congzheng Song
  2. Xinyi Zhou
  3. Doyen Sahoo
  4. Vitaly Shmatikov
  5. Nedim Srndic
  6. Alessandro Bondielli

Papers from Rachel Greenstadt's perspective

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

Their papers