Muli Yang

Computer Vision and Pattern Recognition · 2019

A researcher in the Science corpus: 1 paper; trusts 46 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Muli Yang trusts overall

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

  1. Diederik P. Kingma
  2. Kaiming He
  3. Geoffrey E. Hinton
  4. Yongqin Xian
  5. Alex Krizhevsky
  6. Yoshua Bengio
  7. Jimmy Ba
  8. Individualized Treat
  9. Yann LeCun
  10. Ross B. Girshick

Papers from Muli Yang's perspective

Ordered by how strongly the researchers Muli Yang 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 Large Scale Visual Recognition Challenge
  5. ImageNet: A large-scale hierarchical image database
  6. Long Short-Term Memory
  7. Gradient-based learning applied to document recognition
  8. Attention is All you Need (Neural Information Processing Systems)
  9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  10. Going deeper with convolutions

Their papers