Lin Liu

Artificial Intelligence · with Tang · 2016–2021

A researcher in the Science corpus: 2 papers; trusts 14 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 43 citations into it
• Molecular Biology — 25 citations into it
• General Social Sciences — 5 citations into it
• Information Systems — 5 citations into it
• Natural Language Processing — 5 citations into it
• Probabilistic & Bayesian Methods — 5 citations into it

Whom Lin Liu trusts overall

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

1. David M. Blei
2. Michael I. Jordan
3. Thomas Hofmann
4. T. Griffiths
5. Geoffrey E. Hinton
6. Tom Minka
7. Radford M. Neal
8. Yee Whye Teh
9. Diederik P. Kingma
10. Yoshua Bengio

Papers from Lin Liu's perspective

Ordered by how strongly the researchers Lin Liu 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Attention is All you Need (Neural Information Processing Systems)
5. Gradient-based learning applied to document recognition
6. Long Short-Term Memory
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
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

• Graph Neural Networks and Their Current Applications in Bioinformatics (2021) — 459 citations
• An overview of topic modeling and its current applications in bioinformatics (2016) — 392 citations