Lin Li

Artificial Intelligence · with Hong · 2019–2021

A researcher in the Science corpus: 2 papers; trusts 17 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Lin Li trusts overall

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

  1. David Snyder
  2. Daniel Povey
  3. Diederik P. Kingma
  4. Geoffrey E. Hinton
  5. Kaiming He
  6. Yoon Kim
  7. Florin Curelaru
  8. Alex Krizhevsky
  9. Joon Son Chung
  10. Andrew Zisserman

Papers from Lin Li's perspective

Ordered by how strongly the researchers Lin 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  3. ImageNet classification with deep convolutional neural networks
  4. Attention is All you Need (Neural Information Processing Systems)
  5. Long Short-Term Memory
  6. Dropout: a simple way to prevent neural networks from overfitting
  7. Gradient-based learning applied to document recognition
  8. ImageNet: A large-scale hierarchical image database
  9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  10. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)

Their papers