Yong Liu

Artificial Intelligence · with Zhou · 2022

A researcher in the Science corpus: 1 paper; trusts 4 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Yong Liu trusts overall

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

  1. Diederik P. Kingma
  2. Geoffrey E. Hinton
  3. Karen Simonyan
  4. Kaiming He
  5. Alex Krizhevsky
  6. Yoshua Bengio
  7. Jimmy Ba
  8. Andrew Zisserman
  9. Ilya Sutskever
  10. Nitish Srivastava

Papers from Yong Liu's perspective

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

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

Their papers