Laura Rimell

Artificial Intelligence · 2009–2022

A researcher in the Science corpus: 6 papers; trusts 37 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

Whom Laura Rimell trusts overall

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

  1. Stephen Clark
  2. James Richard Curran
  3. Eugene Charniak
  4. Christopher D. Manning
  5. Marie-Catherine de Marneffe
  6. Richard Socher
  7. Michael Collins
  8. Daniel Klein
  9. Edward Grefenstette
  10. Matthew D. Zeiler

Who trusts Laura Rimell overall

  1. R. Thomas McCoy
  2. Allyson Ettinger
  3. Aakanksha Naik
  4. Tal Linzen
  5. Ellie Pavlick
  6. Eric Wallace
  7. Emily M. Bender
  8. Abhilasha Ravichander
  9. Shuai Tang
  10. Robin Jia

Papers from Laura Rimell's perspective

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

Their papers