Dan Li

Artificial Intelligence · with Chen · 2018–2019

A researcher in the Science corpus: 2 papers; trusts 8 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 21 citations into it; #20,856 of 35,345 by trust here, #12,974 by citations
• Signal Processing — 14 citations into it
• Computer Networks and Communications — 13 citations into it
• Generative Models — 12 citations into it
• Control and Systems Engineering — 9 citations into it; #4,342 of 8,257 by trust here, #3,516 by citations
• Statistics and Probability — 9 citations into it
• Analytical Chemistry — 6 citations into it

Whom Dan Li trusts overall

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

1. Jonathan Goh
2. Individualized Treat
3. Xuewu Dai
4. Thomas Schlegl
5. Aditya P. Mathur
6. Hans-Peter Kriegel
7. Ian T. Jolliffe
8. Aeilko H. Zwinderman
9. Jiawei Han
10. Aleksandar Lazarevic

Who trusts Dan Li overall

1. Niv Cohen
2. Yedid Hoshen
3. Liron Bergman
4. Izhak Golan
5. Ailin Deng
6. Andrew Cook
7. Eunbi Seo
8. Ahmed Abdulaal
9. Zhengwei Wang
10. Murat Sensoy

Papers from Dan Li's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. GENERATIVE ADVERSARIAL NETS
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Gradient-based learning applied to document recognition
6. Improved Techniques for Training GANs
7. Attention is All you Need (Neural Information Processing Systems)
8. Long Short-Term Memory
9. ImageNet: A large-scale hierarchical image database
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• MAD-GAN: Multivariate Anomaly Detection for Time Series Data with Generative Adversarial Networks (2019) — 1,053 citations
• Anomaly Detection with Generative Adversarial Networks for Multivariate Time Series (2018) — 329 citations