Jeremy Gwinnup

Artificial Intelligence · 2014–2019

A researcher in the Science corpus: 6 papers; trusts 49 researchers and is trusted by 7 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 88 citations into it; #18,933 of 35,345 by trust here, #12,761 by citations
• Natural Language Processing — 76 citations into it; #3,258 of 5,688 by trust here, #3,421 by citations
• Computer Vision and Pattern Recognition — 34 citations into it; #11,989 of 21,575 by trust here, #11,286 by citations
• Optimization & Training — 17 citations into it
• Evaluation & Benchmarks — 12 citations into it
• Model Architectures — 8 citations into it

Whom Jeremy Gwinnup trusts overall

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

1. Philipp Koehn
2. Ilya Sutskever
3. Yoshua Bengio
4. Christopher D. Manning
5. Michel Galley
6. Nadir Durrani
7. Oriol Vinyals
8. Geoffrey E. Hinton
9. Kenneth Heafield
10. Dzmitry Bahdanau

Who trusts Jeremy Gwinnup overall

1. Danielle Saunders
2. Bushra Jawaid
3. Shuhao Gu
4. James Thorne
5. Ondrej Bojar
6. Yang Feng

Papers from Jeremy Gwinnup's perspective

Ordered by how strongly the researchers Jeremy Gwinnup 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. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Attention is All you Need (Neural Information Processing Systems)
4. Long Short-Term Memory
5. ImageNet classification with deep convolutional neural networks
6. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
7. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
8. Gradient-based learning applied to document recognition
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

• Overcoming Catastrophic Forgetting During Domain Adaptation of Neural Machine Translation (2019) — 146 citations
• Freezing Subnetworks to Analyze Domain Adaptation in Neural Machine Translation (2018) — 56 citations
• An Empirical Exploration of Curriculum Learning for Neural Machine Translation (2018) — 125 citations
• The AFRL-MITLL WMT16 News-Translation Task Systems (2016) — 5 citations
• The AFRL-MITLL WMT15 System: There’s More than One Way to Decode It! (2015) — 7 citations
• Machine Translation and Monolingual Postediting: The AFRL WMT-14 System (2014) — 17 citations