John Wu

Artificial Intelligence · 2020

A researcher in the Science corpus: 1 paper; trusts 21 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 42 citations into it
• Natural Language Processing — 32 citations into it
• Representation & Self-Supervised Learning — 12 citations into it
• Computer Vision and Pattern Recognition — 11 citations into it
• Large Language Models — 9 citations into it

Whom John Wu trusts overall

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

1. Alec Radford
2. Geoffrey E. Hinton
3. Grzegorz Chrupała
4. Yoshua Bengio
5. Diederik P. Kingma
6. Ilya Sutskever
7. Yonatan Belinkov
8. Richard Socher
9. Alex Krizhevsky
10. Matthew E. Peters

Who trusts John Wu overall

1. Fahim Dalvi
2. Hassan Sajjad

Papers from John Wu's perspective

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

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. Attention is All you Need (Neural Information Processing Systems)
3. ImageNet classification with deep convolutional neural networks
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
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

• Similarity Analysis of Contextual Word Representation Models (2020) — 85 citations