Elinor Poole-Dayan

Artificial Intelligence · 2021

A researcher in the Science corpus: 1 paper; trusts 37 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 26 citations into it
• Safety, Robustness & Interpretability — 20 citations into it
• Natural Language Processing — 19 citations into it
• Large Language Models — 6 citations into it

Whom Elinor Poole-Dayan trusts overall

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

1. Alex Wang
2. Geoffrey E. Hinton
3. Alex Krizhevsky
4. Ilya Sutskever
5. Yoshua Bengio
6. Diederik P. Kingma
7. Kyunghyun Cho
8. Nitish Srivastava
9. Ruslan Salakhutdinov
10. Yann LeCun

Papers from Elinor Poole-Dayan's perspective

Ordered by how strongly the researchers Elinor Poole-Dayan trusts endorse each paper. Same corpus, a different order for every researcher.

1. Attention is All you Need (Neural Information Processing Systems)
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. Long Short-Term Memory
6. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
7. Gradient-based learning applied to document recognition
8. ImageNet: A large-scale hierarchical image database
9. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
10. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)

Their papers

• An Empirical Survey of the Effectiveness of Debiasing Techniques for Pre-trained Language Models (2021) — 165 citations