Matt Le

Artificial Intelligence · with Chen · 2019

A researcher in the Science corpus: 2 papers; trusts 9 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Matt Le trusts overall

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

  1. Philipp Koehn
  2. Geoffrey E. Hinton
  3. Yoshua Bengio
  4. Myle Ott
  5. David Yarowsky
  6. Rico Sennrich
  7. Diederik P. Kingma
  8. Ilya Sutskever
  9. Alex Krizhevsky
  10. Matt Post

Papers from Matt Le's perspective

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

  1. Attention is All you Need (Neural Information Processing Systems)
  2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  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. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
  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. 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