Hang Yan

Computer Vision and Pattern Recognition · with Furukawa · 2019

A researcher in the Science corpus: 1 paper; trusts 8 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Hang Yan trusts overall

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

  1. Kaiming He
  2. Josh Tenenbaum
  3. Sepp Hochreiter
  4. J. Urgen Schmidhuber
  5. Jürgen Sturm
  6. X. Zhang
  7. William T. Freeman
  8. Geoffrey E. Hinton
  9. Adam Paszke
  10. Shaoqing Ren

Papers from Hang Yan's perspective

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

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

Their papers