Joey Liu

Artificial Intelligence · 2016–2019

A researcher in the Science corpus: 6 papers; trusts 36 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 85 citations into it
• Natural Language Processing — 54 citations into it
• Computer Vision and Pattern Recognition — 42 citations into it
• Model Architectures — 20 citations into it
• Medical & Health AI — 14 citations into it
• Reinforcement Learning — 13 citations into it
• Molecular Biology — 10 citations into it
• Optimization & Training — 7 citations into it

Whom Joey Liu trusts overall

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

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

Papers from Joey Liu's perspective

Ordered by how strongly the researchers Joey Liu 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. Long Short-Term Memory
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. ImageNet classification with deep convolutional neural networks
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
8. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
9. ImageNet: A large-scale hierarchical image database
10. Sequence to Sequence Learning with Neural Networks (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
• VQA-Med: Overview of the Medical Visual Question Answering Task at ImageCLEF 2019 (2019) — 322 citations
• Overview of ImageCLEF 2018 Medical Domain Visual Question Answering Task (2018) — 117 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