Lawrence Wolf-Sonkin

Artificial Intelligence · 2019–2020

A researcher in the Science corpus: 4 papers; trusts 6 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

Whom Lawrence Wolf-Sonkin trusts overall

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

  1. Diederik P. Kingma
  2. Paul Baker
  3. Jacob Eisenstein
  4. Geoffrey E. Hinton
  5. David M. Blei
  6. Jimmy Ba
  7. Yoshua Bengio
  8. Mike Schuster
  9. Andrew Y. Ng
  10. M. Bisani

Who trusts Lawrence Wolf-Sonkin overall

  1. Emily Dinan
  2. Adina Williams
  3. Adithya Renduchintala
  4. Karolina Stańczak

Papers from Lawrence Wolf-Sonkin's perspective

Ordered by how strongly the researchers Lawrence Wolf-Sonkin trusts endorse each paper. Same corpus, a different order for every researcher.

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

Their papers