Sheng Chen

Molecular Biology · with Yang · 2019–2022

A researcher in the Science corpus: 3 papers; trusts 15 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Molecular Biology — 56 citations into it
• Artificial Intelligence — 25 citations into it
• Materials Chemistry — 25 citations into it
• Computational Biology & Bioinformatics — 23 citations into it
• Computational Theory and Mathematics — 23 citations into it
• Computer Vision and Pattern Recognition — 17 citations into it
• Model Architectures — 12 citations into it
• Optimization & Training — 8 citations into it

Whom Sheng Chen trusts overall

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

1. Diederik P. Kingma
2. Geoffrey E. Hinton
3. Sepp Hochreiter
4. Kaiming He
5. Martin Steinegger
6. Adam T. Zemla
7. Yoshua Bengio
8. Jimmy Ba
9. J. Urgen Schmidhuber
10. Alex Krizhevsky

Who trusts Sheng Chen overall

1. Zhangyang Gao
2. Chloe Hsu

Papers from Sheng Chen's perspective

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

1. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
2. Long Short-Term Memory
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
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. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
8. ImageNet: A large-scale hierarchical image database
9. Rectified Linear Units Improve Restricted Boltzmann Machines
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• AlphaFold2-aware protein-DNA binding site prediction using graph transformer (2022) — 109 citations
• Predicting drug–protein interaction using quasi-visual question answering system (2019) — 291 citations
• To Improve Protein Sequence Profile Prediction through Image Captioning on Pairwise Residue Distance Map (2019) — 61 citations