Hongbin Lin

Artificial Intelligence · 2021–2022

A researcher in the Science corpus: 2 papers; trusts 89 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Hongbin Lin trusts overall

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

  1. Kaiming He
  2. Geoffrey E. Hinton
  3. Alex Krizhevsky
  4. Yoshua Bengio
  5. Ross B. Girshick
  6. Yann LeCun
  7. Diederik P. Kingma
  8. Eric Tzeng
  9. Ilya Sutskever
  10. Karen Simonyan

Who trusts Hongbin Lin overall

  1. Shuaicheng Niu

Papers from Hongbin Lin's perspective

Ordered by how strongly the researchers Hongbin 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. ImageNet: A large-scale hierarchical image database
  5. Gradient-based learning applied to document recognition
  6. Attention is All you Need (Neural Information Processing Systems)
  7. ImageNet Large Scale Visual Recognition Challenge
  8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  9. Long Short-Term Memory
  10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers