Quan Le

Molecular Biology · 2020

A researcher in the Science corpus: 1 paper; trusts 51 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Molecular Biology — 68 citations into it
• Computational Biology & Bioinformatics — 34 citations into it
• Materials Chemistry — 30 citations into it
• Model Architectures — 11 citations into it
• Computational Theory and Mathematics — 8 citations into it

Whom Quan Le trusts overall

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

1. Gianluca Pollastri
2. Burkhard Rost
3. Pierre Baldi
4. David T. Jones
5. Jianlin Cheng
6. David C. Jones
7. Sean R. Eddy
8. Geoffrey E. Hinton
9. Martin Steinegger
10. Peter Tompa

Papers from Quan Le's perspective

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

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

Their papers

• Deep learning methods in protein structure prediction (2020) — 239 citations