S. Pradhan

Artificial Intelligence · 2005–2019

A researcher in the Science corpus: 2 papers; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom S. Pradhan trusts overall

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

  1. Scott Aaronson
  2. Simon S. Haykin

Papers from S. Pradhan's perspective

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

  1. GradientBased Learning Applied to Document Recognition
  2. Unsupervised Learning of Invariant Feature Hierarchies with Applications to Object Recognition
  3. Read the fine print (Nature Physics)
  4. Gradient-based learning applied to document recognition
  5. ImageNet classification with deep convolutional neural networks
  6. Long Short-Term Memory
  7. Attention is All you Need (Neural Information Processing Systems)
  8. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  9. Learning Multiple Layers of Features from Tiny Images
  10. Distinctive Image Features from Scale-Invariant Keypoints

Their papers