David Gaddy

Artificial Intelligence · 2016–2018

A researcher in the Science corpus: 2 papers; trusts 31 researchers and is trusted by 11 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 37 citations into it; #14,817 of 35,345 by trust here, #22,463 by citations
• Natural Language Processing — 32 citations into it; #2,721 of 5,688 by trust here, #4,250 by citations
• Model Architectures — 6 citations into it

Whom David Gaddy trusts overall

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

1. Daniel Klein
2. Slav Petrov
3. Eugene Charniak
4. Christopher D. Manning
5. Tomas Mikolov
6. Michael Collins
7. Geoffrey E. Hinton
8. Yoshua Bengio
9. Mitchell P. Marcus
10. Ilya Sutskever

Who trusts David Gaddy overall

1. Nikita Kitaev
2. Daniel Klein
3. Mikel Artetxe
4. Antonios Anastasopoulos
5. David Alvarez-Melis
6. Meng Fang
7. Yonatan Belinkov
8. Zihan Liu
9. Meng Zhang

Papers from David Gaddy's perspective

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

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

Their papers

• Ten Pairs to Tag – Multilingual POS Tagging via Coarse Mapping between Embeddings (2016) — 124 citations
• What’s Going On in Neural Constituency Parsers? An Analysis (2018) — 76 citations