Emily Sheng

Artificial Intelligence · 2019–2021

A researcher in the Science corpus: 8 papers; trusts 224 researchers and is trusted by 33 researchers here, as inferred from the citation graph.

Subfields

Whom Emily Sheng trusts overall

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

  1. Alec Radford
  2. Kai-Wei Chang
  3. Jieyu Zhao
  4. Geoffrey E. Hinton
  5. Yoshua Bengio
  6. Ilya Sutskever
  7. Diederik P. Kingma
  8. Jacob Devlin
  9. Alex Krizhevsky
  10. Kaiming He

Who trusts Emily Sheng overall

  1. Eric Michael Smith
  2. Kai-Wei Chang
  3. Sunipa Dev
  4. Nanyun Peng
  5. Percy Liang
  6. Emily Dinan
  7. Premkumar Natarajan
  8. Adina Williams
  9. Yejin Choi
  10. Melanie Kambadur

Papers from Emily Sheng's perspective

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

  1. Attention is All you Need (Neural Information Processing Systems)
  2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  4. ImageNet classification with deep convolutional neural networks
  5. Long Short-Term Memory
  6. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
  7. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
  8. ImageNet: A large-scale hierarchical image database
  9. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
  10. Gradient-based learning applied to document recognition

Their papers