Toms Bergmanis

Natural Language Processing · 2020

A researcher in the Science corpus: 1 paper; trusts 28 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

• Natural Language Processing — 29 citations into it; #3,605 of 5,688 by trust here, #4,682 by citations
• Artificial Intelligence — 27 citations into it; #21,156 of 35,345 by trust here, #25,809 by citations
• Safety, Robustness & Interpretability — 11 citations into it

Whom Toms Bergmanis trusts overall

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

1. Philipp Koehn
2. Matt Post
3. Rico Sennrich
4. Christopher D. Manning
5. Kevin Clark
6. Chris Dyer
7. Paul Michel
8. Yoshua Bengio
9. Geoffrey E. Hinton
10. Danielle Saunders

Who trusts Toms Bergmanis overall

1. Karolina Stańczak
2. Danielle Saunders
3. Emily Sheng
4. Isabelle Augenstein
5. Rosie Sallis
6. Kai-Wei Chang
7. Bill Byrne
8. Adithya Renduchintala

Papers from Toms Bergmanis's perspective

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

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

Their papers

• Mitigating Gender Bias in Machine Translation with Target Gender Annotations (2020) — 69 citations