Betty van Aken

Artificial Intelligence · 2018–2019

A researcher in the Science corpus: 2 papers; trusts 56 researchers and is trusted by 7 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 64 citations into it; #17,549 of 35,345 by trust here, #17,110 by citations
• Natural Language Processing — 49 citations into it; #3,076 of 5,688 by trust here, #3,478 by citations
• Information Systems — 20 citations into it
• Safety, Robustness & Interpretability — 20 citations into it; #1,163 of 2,251 by trust here, #1,673 by citations
• Communication — 12 citations into it
• Representation & Self-Supervised Learning — 11 citations into it
• Computer Vision and Pattern Recognition — 7 citations into it
• Large Language Models — 5 citations into it

Whom Betty van Aken trusts overall

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

1. Geoffrey E. Hinton
2. Alec Radford
3. Yoshua Bengio
4. Ziqi Zhang
5. Tomas Mikolov
6. Diederik P. Kingma
7. Ilya Sutskever
8. Alex Krizhevsky
9. Richard Socher
10. Zeerak Talat

Who trusts Betty van Aken overall

1. Yangjun Zhang
2. Svetlana Kiritchenko
3. Ammar Mohammed
4. Anna Rogers
5. Michael Wiegand
6. Keita Kurita
7. Pengjie Ren
8. Isar Nejadgholi
9. Maarten Sap
10. Jiawen Deng

Papers from Betty van Aken's perspective

Ordered by how strongly the researchers Betty van Aken 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. ImageNet classification with deep convolutional neural networks
3. Attention is All you Need (Neural Information Processing Systems)
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
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

• Challenges for Toxic Comment Classification: An In-Depth Error Analysis (2018) — 250 citations
• How Does BERT Answer Questions?: A Layer-Wise Analysis of Transformer Representations (2019) — 186 citations