Ben Burtenshaw

Artificial Intelligence · 2021

A researcher in the Science corpus: 1 paper; trusts 17 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 9 citations into it
• Natural Language Processing — 6 citations into it

Whom Ben Burtenshaw trusts overall

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

1. Guillaume Lample
2. Sepp Hochreiter
3. James Bergstra
4. Yoshua Bengio
5. Jacob Devlin
6. Trevor J. Hastie
7. J. Urgen Schmidhuber
8. Marc'Aurelio Ranzato
9. Ashish Vaswani
10. Alexis Conneau

Papers from Ben Burtenshaw's perspective

Ordered by how strongly the researchers Ben Burtenshaw 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. Attention is All you Need (Neural Information Processing Systems)
4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Gradient-based learning applied to document recognition
7. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
8. ImageNet: A large-scale hierarchical image database
9. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• A Dutch Dataset for Cross-lingual Multilabel Toxicity Detection (2021) — 8 citations