Blake Shaw

Computer Vision and Pattern Recognition · 2007–2013

A researcher in the Science corpus: 3 papers; trusts 18 researchers and is trusted by 9 researchers here, as inferred from the citation graph.

Subfields

Whom Blake Shaw trusts overall

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

  1. Kilian Q. Weinberger
  2. Lawrence K. Saul
  3. Josh Tenenbaum
  4. David A. Sontag
  5. S. Burer
  6. Thomas Finley
  7. Sanjeev Arora
  8. Thorsten Joachims
  9. Geoffrey E. Hinton
  10. Tommi S. Jaakkola

Who trusts Blake Shaw overall

  1. Ehsan Elhamifar
  2. Tuan M. V. Le
  3. L. V. D. van der Maaten
  4. Zheng Zhao
  5. K. Jia
  6. René Vidal
  7. Tony Jebara
  8. Hady W. Lauw
  9. Liwei Wang
  10. Eric O. Postma

Papers from Blake Shaw's perspective

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

Their papers