Chan Ho So

Artificial Intelligence · 2018–2019

A researcher in the Science corpus: 2 papers; trusts 25 researchers and is trusted by 9 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 36 citations into it; #14,158 of 35,345 by trust here, #4,466 by citations
• Natural Language Processing — 23 citations into it; #2,632 of 5,688 by trust here, #1,089 by citations
• Molecular Biology — 22 citations into it; #4,781 of 17,773 by trust here, #2,983 by citations
• Model Architectures — 6 citations into it
• Computer Vision and Pattern Recognition — 5 citations into it

Whom Chan Ho So trusts overall

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

1. Robert Leaman
2. Geoffrey E. Hinton
3. Yoshua Bengio
4. Tomas Mikolov
5. Dzmitry Bahdanau
6. Mike Schuster
7. John C. Duchi
8. Alex Krizhevsky
9. Lev-Arie Ratinov
10. Ilya Sutskever

Who trusts Chan Ho So overall

1. M. V. Koroteev
2. Iz Beltagy

Papers from Chan Ho So's perspective

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

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

Their papers

• BioBERT: a pre-trained biomedical language representation model for biomedical text mining (2019) — 7,641 citations
• CollaboNet: collaboration of deep neural networks for biomedical named entity recognition (2018) — 147 citations