Didier Schwab

Artificial Intelligence · 2017–2021

A researcher in the Science corpus: 4 papers; trusts 47 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Didier Schwab trusts overall

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

  1. Tomas Mikolov
  2. Geoffrey E. Hinton
  3. Yoshua Bengio
  4. Ronan Collobert
  5. Ilya Sutskever
  6. Diederik P. Kingma
  7. Andriy Mnih
  8. J. Ross Quinlan
  9. Yann LeCun
  10. Alex Krizhevsky

Papers from Didier Schwab's perspective

Ordered by how strongly the researchers Didier Schwab 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. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
  6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  7. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
  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. Distributed Representations of Words and Phrases and their Compositionality (Neural Information Processing Systems)

Their papers