Kathy Lee

Artificial Intelligence · 2016–2018

A researcher in the Science corpus: 4 papers; trusts 25 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 71 citations into it
• Natural Language Processing — 48 citations into it
• Medical & Health AI — 14 citations into it
• Model Architectures — 14 citations into it
• Reinforcement Learning — 13 citations into it
• Molecular Biology — 10 citations into it
• Management Science and Operations Research — 6 citations into it
• Optimization & Training — 5 citations into it

Whom Kathy Lee trusts overall

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

1. Diederik P. Kingma
2. Richard S. Sutton
3. Yoshua Bengio
4. Geoffrey E. Hinton
5. Edward Choi
6. Richard Bellman
7. Ilya Sutskever
8. Alex Krizhevsky
9. Jimmy Ba
10. Alex Graves

Papers from Kathy Lee's perspective

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

1. Long Short-Term Memory
2. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. ImageNet classification with deep convolutional neural networks
5. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
6. Attention is All you Need (Neural Information Processing Systems)
7. Gradient-based learning applied to document recognition
8. ImageNet: A large-scale hierarchical image database
9. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
10. Distributed Representations of Words and Phrases and their Compositionality (Neural Information Processing Systems)

Their papers

• DR-BiLSTM: Dependent Reading Bidirectional LSTM for Natural Language Inference (2018) — 105 citations
• Condensed Memory Networks for Clinical Diagnostic Inferencing (2016) — 108 citations
• Learning to Diagnose: Assimilating Clinical Narratives using Deep Reinforcement Learning (2017) — 29 citations
• Diagnostic Inferencing via Improving Clinical Concept Extraction with Deep Reinforcement Learning: A Preliminary Study (2017) — 43 citations