Song Li

Artificial Intelligence · with Hong · 2021

A researcher in the Science corpus: 1 paper; trusts 4 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Song Li trusts overall

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

  1. Yoon Kim
  2. A. de Cheveigné
  3. Ryuichi Yamamoto
  4. Hideyuki Tachibana
  5. Daniel Povey
  6. David Snyder
  7. Naihan Li
  8. Alexander M. Rush
  9. Hideki Kawahara
  10. Yuxuan Wang

Papers from Song Li's perspective

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

  1. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  3. Attention is All you Need (Neural Information Processing Systems)
  4. ImageNet classification with deep convolutional neural networks
  5. Long Short-Term Memory
  6. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
  7. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
  8. Gradient-based learning applied to document recognition
  9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  10. ImageNet: A large-scale hierarchical image database

Their papers