John Pougué-Biyong

Artificial Intelligence · 2021

A researcher in the Science corpus: 1 paper; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom John Pougué-Biyong trusts overall

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

  1. Jure Leskovec
  2. William L. Hamilton
  3. Jiliang Tang
  4. Aditya Grover
  5. Jacob Devlin
  6. Dan Huttenlocher
  7. Geoffrey E. Hinton
  8. Yoshua Bengio
  9. Tyler Derr
  10. Diederik P. Kingma

Papers from John Pougué-Biyong's perspective

Ordered by how strongly the researchers John Pougué-Biyong trusts endorse each paper. Same corpus, a different order for every researcher.

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

Their papers