Thomas H. Li

Computer Vision and Pattern Recognition · 2019

A researcher in the Science corpus: 2 papers; trusts 207 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Thomas H. Li trusts overall

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

  1. Diederik P. Kingma
  2. Geoffrey E. Hinton
  3. Kaiming He
  4. Alex Krizhevsky
  5. Karen Simonyan
  6. Andrew Zisserman
  7. Yann LeCun
  8. Yoshua Bengio
  9. Alexei A. Efros
  10. Ross B. Girshick

Papers from Thomas H. Li's perspective

Ordered by how strongly the researchers Thomas H. Li 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. Gradient-based learning applied to document recognition
  5. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  6. Attention is All you Need (Neural Information Processing Systems)
  7. ImageNet: A large-scale hierarchical image database
  8. Long Short-Term Memory
  9. Going deeper with convolutions
  10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers