Kai Song

Molecular Biology · 2020

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

Subfields

• Molecular Biology — 25 citations into it
• Ecology — 10 citations into it

Whom Kai Song trusts overall

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

1. Derrick E. Fouts
2. Diederik P. Kingma
3. Daniel Quang
4. Dan Hendrycks
5. Jian Zhou

Papers from Kai Song's perspective

Ordered by how strongly the researchers Kai Song 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. ImageNet classification with deep convolutional neural networks
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Gradient-based learning applied to document recognition
5. Long Short-Term Memory
6. Learning Multiple Layers of Features from Tiny Images
7. Attention is All you Need (Neural Information Processing Systems)
8. ImageNet: A large-scale hierarchical image database
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Identifying viruses from metagenomic data using deep learning (2020) — 553 citations