Jin Li

Molecular Biology · with McPartlon · 2019–2020

A researcher in the Science corpus: 2 papers; trusts 45 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Molecular Biology — 48 citations into it
• Computational Biology & Bioinformatics — 36 citations into it
• Materials Chemistry — 15 citations into it
• Model Architectures — 8 citations into it
• Artificial Intelligence — 7 citations into it
• Spectroscopy — 7 citations into it
• Optimization & Training — 5 citations into it

Whom Jin Li trusts overall

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

1. Mohammed Alquraishi
2. Yang Zhang
3. Ashish Vaswani
4. Razvan Pascanu
5. Peter Shaw
6. Yoshua Bengio
7. Jakob Uszkoreit
8. Sheng Wang
9. Geoffrey E. Hinton
10. Jeffrey Skolnick

Who trusts Jin Li overall

1. Ratul Chowdhury
2. Krzysztof Marcin Choromanski

Papers from Jin Li's perspective

Ordered by how strongly the researchers Jin Li 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. Attention is All you Need (Neural Information Processing Systems)
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Going deeper with convolutions
9. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Improved protein structure prediction by deep learning irrespective of co-evolution information (2020) — 210 citations
• Universal Transforming Geometric Network (2019) — 9 citations