Roopak Shah

1993

A researcher in the Science corpus: 1 paper; trusts 1 researcher and is trusted by 292 researchers here, as inferred from the citation graph.

Whom Roopak Shah trusts

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

  1. Yann LeCun (in Statistical Learning Theory)

Who trusts Roopak Shah

  1. Luc Van Gool (in Computer Vision and Pattern Recognition)
  2. Trevor Darrell (in Computer Vision and Pattern Recognition)
  3. Kristen Grauman (in Computer Vision and Pattern Recognition)
  4. Xiaogang Wang (in Computer Vision and Pattern Recognition)
  5. Yi Yang (in Computer Vision and Pattern Recognition)
  6. Dacheng Tao (in Computer Vision and Pattern Recognition)
  7. Andrea Vedaldi (in Computer Vision and Pattern Recognition)
  8. Bernt Schiele (in Computer Vision and Pattern Recognition)
  9. Andrew Zisserman (in Computer Vision and Pattern Recognition)
  10. Yoshua Bengio (in Computer Vision and Pattern Recognition)

Papers from Roopak Shah's perspective

Ordered by how strongly the researchers Roopak Shah trusts endorse each paper. Same corpus, a different order for every researcher.

  1. Generalization and network design strategies
  2. Neural Networks for Fingerprint Recognition
  3. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  4. Learning Multiple Layers of Features from Tiny Images
  5. Dropout: a simple way to prevent neural networks from overfitting
  6. Greedy Layer-Wise Training of Deep Networks
  7. Gradient-based learning applied to document recognition
  8. Distilling the Knowledge in a Neural Network (arXiv.org)
  9. An Input Output HMM Architecture
  10. GENERATIVE ADVERSARIAL NETS

Their papers