Haibin Lin

Artificial Intelligence · 2019–2020

A researcher in the Science corpus: 4 papers; trusts 216 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Haibin Lin trusts overall

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

  1. Alex Krizhevsky
  2. Kaiming He
  3. Sebastian U. Stich
  4. Geoffrey E. Hinton
  5. Ross B. Girshick
  6. Yann LeCun
  7. Yoshua Bengio
  8. Diederik P. Kingma
  9. Christian Szegedy
  10. Ilya Sutskever

Papers from Haibin Lin's perspective

Ordered by how strongly the researchers Haibin Lin 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  4. Gradient-based learning applied to document recognition
  5. ImageNet: A large-scale hierarchical image database
  6. Attention is All you Need (Neural Information Processing Systems)
  7. Learning Multiple Layers of Features from Tiny Images
  8. ImageNet Large Scale Visual Recognition Challenge
  9. Long Short-Term Memory
  10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers