Zai Huang

Artificial Intelligence · 2018–2019

A researcher in the Science corpus: 2 papers; trusts 9 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Zai Huang trusts overall

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

  1. Alex Graves
  2. Alex Krizhevsky
  3. Geoffrey E. Hinton
  4. Diederik P. Kingma
  5. Ilya Sutskever
  6. Andrew G. Howard
  7. Robert Hecht-Nielsen
  8. Tomas Mikolov
  9. Yoshua Bengio
  10. Jimmy Ba

Papers from Zai Huang's perspective

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

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

Their papers