Yu-Ru Lin

Artificial Intelligence · 2008–2019

A researcher in the Science corpus: 6 papers; trusts 54 researchers and is trusted by 11 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 38 citations into it; #21,084 of 35,345 by trust here, #15,542 by citations
• Statistical and Nonlinear Physics — 35 citations into it; #4,818 of 10,127 by trust here, #2,928 by citations
• Computer Vision and Pattern Recognition — 18 citations into it
• Sociology and Political Science — 18 citations into it; #10,125 of 22,756 by trust here, #14,917 by citations
• Information Systems — 11 citations into it
• Safety, Robustness & Interpretability — 10 citations into it
• Safety Research — 8 citations into it; #3,319 of 5,829 by trust here, #4,580 by citations
• Statistics and Probability — 8 citations into it

Whom Yu-Ru Lin trusts overall

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

1. Jon M. Kleinberg
2. Mark Newman
3. Jure Leskovec
4. Inderjit S. Dhillon
5. Jerome H. Friedman
6. Jianbo Shi
7. Ravi Kumar
8. Geoffrey E. Hinton
9. John C. Gower
10. Qiaozhu Mei

Who trusts Yu-Ru Lin overall

1. Santo Fortunato
2. Tianbao Yang
3. Ruibo Liu
4. Lei Tang
5. Axel Bruns
6. Yun Chi
7. Symeon Papadopoulos
8. Shenghuo Zhu
9. Huan Liu
10. Dang Lien Minh

Papers from Yu-Ru Lin's perspective

Ordered by how strongly the researchers Yu-Ru Lin 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. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Long Short-Term Memory
5. Gradient-based learning applied to document recognition
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. Et al
9. Going deeper with convolutions
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• More Voices Than Ever? Quantifying Media Bias in Networks (2011) — 73 citations
• FairSight: Visual Analytics for Fairness in Decision Making (2019) — 149 citations
• Recipe recommendation using ingredient networks (2011) — 300 citations
• How Does the Data Sampling Strategy Impact the Discovery of Information Diffusion in Social Media? (2010) — 242 citations
• Analyzing communities and their evolutions in dynamic social networks (2009) — 311 citations
• Facetnet: a framework for analyzing communities and their evolutions in dynamic networks (2008) — 443 citations