Duncan A. J. Blythe

Artificial Intelligence · 2018–2019

A researcher in the Science corpus: 2 papers; trusts 56 researchers and is trusted by 52 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 41 citations into it; #34,750 of 35,345 by trust here, #22,463 by citations
• Natural Language Processing — 38 citations into it; #1,169 of 5,688 by trust here, #1,975 by citations
• Representation & Self-Supervised Learning — 13 citations into it
• Model Architectures — 10 citations into it
• Computer Vision and Pattern Recognition — 9 citations into it
• Evaluation & Benchmarks — 5 citations into it

Whom Duncan A. J. Blythe trusts overall

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

1. Ilya Sutskever
2. Alex Graves
3. Geoffrey E. Hinton
4. Yoshua Bengio
5. Sepp Hochreiter
6. Tomas Mikolov
7. Matthew E. Peters
8. Michael Collins
9. Oriol Vinyals
10. Diederik P. Kingma

Who trusts Duncan A. J. Blythe overall

1. Jinlan Fu
2. Alan Akbik
3. Jonas Pfeiffer
4. Xinyu Wang
5. Branden Chan
6. Han He
7. Wee Chung Gan
8. Zining Zhu
9. Ninareh Mehrabi
10. Fábio Souza

Papers from Duncan A. J. Blythe's perspective

Ordered by how strongly the researchers Duncan A. J. Blythe trusts endorse each paper. Same corpus, a different order for every researcher.

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

Their papers

• FLAIR: An Easy-to-Use Framework for State-of-the-Art NLP (2019) — 933 citations
• Contextual String Embeddings for Sequence Labeling (2018) — 1,382 citations