Nathaniel J. Smith

Artificial Intelligence · 2013–2017

A researcher in the Science corpus: 2 papers; trusts 30 researchers and is trusted by 10 researchers here, as inferred from the citation graph.

Subfields

Whom Nathaniel J. Smith trusts overall

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

  1. Joshua Goodman
  2. Alan Y. Chiang
  3. Dennis Norris
  4. Keith Rayner
  5. Simon N. Wood
  6. H. Baayen
  7. Reinhard Kneser
  8. Joshua I. Gold
  9. Vera Demberg
  10. Reinhold Kliegl

Who trusts Nathaniel J. Smith overall

  1. Stefan Gries
  2. Rajakrishnan Rajkumar
  3. Ethan Gotlieb Wilcox
  4. Micha Heilbron
  5. Nick C. Ellis
  6. Richard Futrell
  7. Marten van Schijndel
  8. Roger Levy
  9. Kristijan Armeni
  10. T. Florian Jaeger

Papers from Nathaniel J. Smith's perspective

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

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

Their papers