Qing Ye

Molecular Biology · 2017

A researcher in the Science corpus: 1 paper; trusts 23 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Molecular Biology — 36 citations into it
• Computational Biology & Bioinformatics — 28 citations into it
• Materials Chemistry — 17 citations into it
• Artificial Intelligence — 6 citations into it
• Computer Vision and Pattern Recognition — 5 citations into it
• Evaluation & Benchmarks — 5 citations into it

Whom Qing Ye trusts overall

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

1. Yang Zhang
2. Sergey Ovchinnikov
3. John Moult
4. Geoffrey E. Hinton
5. Matthew D. Zeiler
6. Sean R. Eddy
7. Diederik P. Kingma
8. Thomas A. Hopf
9. David T. Jones
10. Ilya Sutskever

Papers from Qing Ye's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
3. Gradient-based learning applied to document recognition
4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
5. Attention is All you Need (Neural Information Processing Systems)
6. Long Short-Term Memory
7. Learning Multiple Layers of Features from Tiny Images
8. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
9. Deep Learning
10. Fully convolutional networks for semantic segmentation

Their papers

• Enhancing Evolutionary Couplings with Deep Convolutional Neural Networks (2017) — 113 citations