Nathan Greenberg

Artificial Intelligence · 2018

A researcher in the Science corpus: 1 paper; trusts 4 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Nathan Greenberg trusts overall

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

  1. Robert Leaman
  2. Chih-Hsuan Wei
  3. Zhiyong Lu
  4. John D. Lafferty
  5. Rico Sennrich
  6. Yifan Peng
  7. Andrew McCallum
  8. Guillaume Lample
  9. R. Caruana
  10. Jiao Li

Who trusts Nathan Greenberg overall

  1. Jonas Pfeiffer
  2. Natawut Monaikul
  3. Edwin Simpson
  4. Giuseppe Castellucci

Papers from Nathan Greenberg's perspective

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

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

Their papers