Guanhong Tao

Artificial Intelligence · 2019

A researcher in the Science corpus: 1 paper; trusts 11 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Guanhong Tao trusts overall

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

  1. Alex Krizhevsky
  2. Karen Simonyan
  3. Kaiming He
  4. Andrew Zisserman
  5. Geoffrey E. Hinton
  6. Jia Deng
  7. Yann LeCun
  8. Ross B. Girshick
  9. Simon S. Haykin

Papers from Guanhong Tao's perspective

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

Their papers