Gang Huang

Artificial Intelligence · 2016–2020

A researcher in the Science corpus: 3 papers; trusts 39 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Gang Huang trusts overall

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

  1. Tien-Ju Yang
  2. Jia Deng
  3. Kaiming He
  4. Alex Krizhevsky
  5. Geoffrey E. Hinton
  6. Andrew G. Howard
  7. H. Brendan McMahan
  8. Yoshua Bengio

Papers from Gang Huang's perspective

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

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

Their papers