Shuangjia Zheng

Molecular Biology · 2019–2022

A researcher in the Science corpus: 5 papers; trusts 25 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Molecular Biology — 95 citations into it
• Computational Theory and Mathematics — 69 citations into it
• Materials Chemistry — 40 citations into it
• Artificial Intelligence — 33 citations into it
• Computer Vision and Pattern Recognition — 32 citations into it
• Computational Biology & Bioinformatics — 30 citations into it
• Computational Chemistry & Drug Discovery — 26 citations into it
• Model Architectures — 15 citations into it

Whom Shuangjia Zheng trusts overall

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

1. Geoffrey E. Hinton
2. Sepp Hochreiter
3. Kaiming He
4. Alex Krizhevsky
5. Vinod Nair
6. Diederik P. Kingma
7. Yoshua Bengio
8. J. Urgen Schmidhuber
9. Ilya Sutskever
10. David Ryan Koes

Who trusts Shuangjia Zheng overall

1. Kenneth Atz
2. Francesca Grisoni

Papers from Shuangjia Zheng's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Long Short-Term Memory
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Going deeper with convolutions
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Structure-Aware Multimodal Deep Learning for Drug-Protein Interaction Prediction (2022) — 65 citations
• TANKBind: Trigonometry-Aware Neural NetworKs for Drug-Protein Binding Structure Prediction (2022) — 237 citations
• 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
• Deep Learning Enables Accurate Diagnosis of Novel Coronavirus (COVID-19) With CT Images (2020) — 836 citations