Kyle Young

2019

A researcher in the Science corpus: 1 paper; trusts 1 researcher and is trusted by 0 researchers here, as inferred from the citation graph.

Whom Kyle Young trusts overall

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

  1. Lloyd S. Shapley
  2. Scott M. Lundberg
  3. Kjersti Aas
  4. Jianbo Chen
  5. Ramprasaath R. Selvaraju
  6. Julius Adebayo
  7. Su-In Lee
  8. Le Song

Who trusts Kyle Young overall

  1. Wojciech Samek
  2. Grgoire Montavon

Papers from Kyle Young's perspective

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

  1. ImageNet classification with deep convolutional neural networks
  2. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  4. Gradient-based learning applied to document recognition
  5. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  6. ImageNet: A large-scale hierarchical image database
  7. ImageNet Large Scale Visual Recognition Challenge
  8. Learning Multiple Layers of Features from Tiny Images
  9. Attention is All you Need (Neural Information Processing Systems)
  10. Long Short-Term Memory

Their papers