Rebecca Knowles

Artificial Intelligence · with Koehn · 2016–2017

A researcher in the Science corpus: 2 papers; trusts 62 researchers and is trusted by 121 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 34 citations into it; #2,223 of 35,345 by trust here, #5,187 by citations
• Natural Language Processing — 30 citations into it; #545 of 5,688 by trust here, #1,182 by citations
• Computer Vision and Pattern Recognition — 12 citations into it; #3,248 of 21,575 by trust here, #3,875 by citations
• Model Architectures — 5 citations into it

Whom Rebecca Knowles trusts overall

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

1. Rico Sennrich
2. Ilya Sutskever
3. Dzmitry Bahdanau
4. Kyunghyun Cho
5. Yoshua Bengio
6. Barry Haddow
7. Oriol Vinyals
8. Geoffrey E. Hinton
9. Philipp Koehn
10. Spence Green

Who trusts Rebecca Knowles overall

1. Timo Schick
2. Graham Neubig
3. Chris Hokamp
4. Philipp Koehn
5. Hinrich Schütze
6. Mikel Artetxe
7. Tsz Kin Lam
8. Rico Sennrich
9. Felix Stahlberg
10. Huda Khayrallah

Papers from Rebecca Knowles's perspective

Ordered by how strongly the researchers Rebecca Knowles 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. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
7. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
8. Gradient-based learning applied to document recognition
9. ImageNet: A large-scale hierarchical image database
10. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)

Their papers

• Six Challenges for Neural Machine Translation (2017) — 1,374 citations
• Neural Interactive Translation Prediction (2016) — 90 citations