Wenjie Shu

Molecular Biology · 2016–2018

A researcher in the Science corpus: 2 papers; trusts 11 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Molecular Biology — 60 citations into it
• Artificial Intelligence — 47 citations into it
• Computer Vision and Pattern Recognition — 35 citations into it
• Optimization & Training — 19 citations into it
• Natural Language Processing — 7 citations into it
• Probabilistic & Bayesian Methods — 5 citations into it

Whom Wenjie Shu trusts overall

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

1. Geoffrey E. Hinton
2. Paul J. Werbos
3. Alex Graves
4. Yoshua Bengio
5. J. Urgen Schmidhuber
6. Yann LeCun
7. Alex Krizhevsky
8. Ilya Sutskever
9. David E. Rumelhart
10. L. Eon Bottou

Papers from Wenjie Shu's perspective

Ordered by how strongly the researchers Wenjie Shu 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. Gradient-based learning applied to document recognition
4. Long Short-Term Memory
5. Going deeper with convolutions
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. Attention is All you Need (Neural Information Processing Systems)
8. Dropout: a simple way to prevent neural networks from overfitting
9. Learning Multiple Layers of Features from Tiny Images
10. ImageNet: A large-scale hierarchical image database

Their papers

• PEDLA: predicting enhancers with a deep learning-based algorithmic framework (2016) — 111 citations
• Deep Learning and Its Applications in Biomedicine (2018) — 524 citations