Bailey Kuehl

Artificial Intelligence · 2020–2021

A researcher in the Science corpus: 2 papers; trusts 19 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Bailey Kuehl trusts overall

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

  1. Diederik P. Kingma
  2. Geoffrey E. Hinton
  3. Iz Beltagy
  4. Chin-Yew Lin
  5. Michael Lewis
  6. Yoshua Bengio
  7. Jianhua Lin
  8. Alex Krizhevsky
  9. Jimmy Ba
  10. Ilya Sutskever

Papers from Bailey Kuehl's perspective

Ordered by how strongly the researchers Bailey Kuehl 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. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
  3. Attention is All you Need (Neural Information Processing Systems)
  4. Long Short-Term Memory
  5. ImageNet classification with deep convolutional neural networks
  6. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  7. Dropout: a simple way to prevent neural networks from overfitting
  8. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
  9. ImageNet: A large-scale hierarchical image database
  10. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)

Their papers