Alap Karapurkar

Computer Vision and Pattern Recognition · 2008

A researcher in the Science corpus: 1 paper; trusts 8 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

Whom Alap Karapurkar trusts overall

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

  1. Julian Besag
  2. Daniel Scharstein
  3. Yair Weiss
  4. Andreas Klaus
  5. William T. Freeman

Who trusts Alap Karapurkar overall

  1. Lucas Theis
  2. Daniel Zoran
  3. Tim Salimans

Papers from Alap Karapurkar's perspective

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

  1. What makes a good model of natural images? (2007 IEEE Conference on Computer Vision and Pattern Recognition)
  2. Statistical Analysis of Non-Lattice Data
  3. Learning Conditional Random Fields for Stereo
  4. The Nature of Statistical Learning
  5. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  6. Segment-Based Stereo Matching Using Belief Propagation and a Self-Adapting Dissimilarity Measure (International Conference on Pattern Recognition)
  7. Gradient-based learning applied to document recognition
  8. ImageNet classification with deep convolutional neural networks
  9. ImageNet: A large-scale hierarchical image database
  10. Learning Multiple Layers of Features from Tiny Images

Their papers