John Bauer

Natural Language Processing · 2013–2017

A researcher in the Science corpus: 4 papers; trusts 16 researchers and is trusted by 234 researchers here, as inferred from the citation graph.

Subfields

Whom John Bauer trusts overall

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

  1. Eugene Charniak
  2. Daniel Klein
  3. Christopher D. Manning
  4. Richard Socher
  5. Nathan D. Ratliff
  6. Michael Collins
  7. Yoshua Bengio
  8. Andrew Y. Ng
  9. Geoffrey E. Hinton
  10. Slav Petrov

Who trusts John Bauer overall

  1. Richard Socher
  2. Yoav Goldberg
  3. John Wieting
  4. Duyu Tang
  5. Christopher D. Manning
  6. Mohit Bansal
  7. Percy Liang
  8. Caiming Xiong
  9. Samuel R. Bowman
  10. Amir Zeldes

Papers from John Bauer's perspective

Ordered by how strongly the researchers John Bauer 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. Long Short-Term Memory
  4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  5. Attention is All you Need (Neural Information Processing Systems)
  6. Gradient-based learning applied to document recognition
  7. ImageNet: A large-scale hierarchical image database
  8. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
  9. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
  10. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)

Their papers