Di Huang

Artificial Intelligence · with Ding · 2021

A researcher in the Science corpus: 1 paper; trusts 22 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

Whom Di Huang trusts overall

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

  1. Alex Krizhevsky
  2. Paul Bergmann
  3. Geoffrey E. Hinton
  4. Thomas Schlegl

Who trusts Di Huang overall

  1. Hanqiu Deng
  2. Xingyu Li

Papers from Di Huang's perspective

Ordered by how strongly the researchers Di Huang 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. Gradient-based learning applied to document recognition
  3. Learning Multiple Layers of Features from Tiny Images
  4. ImageNet classification with deep convolutional neural networks
  5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  6. Reading Digits in Natural Images with Unsupervised Feature Learning
  7. Visualizing and Understanding Convolutional Networks
  8. Attention is All you Need (Neural Information Processing Systems)
  9. GENERATIVE ADVERSARIAL NETS
  10. ImageNet: A large-scale hierarchical image database

Their papers