Liyang Xie

Artificial Intelligence · 2017–2018

A researcher in the Science corpus: 2 papers; trusts 34 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 43 citations into it; #29,735 of 35,345 by trust here, #27,551 by citations
• Computer Vision and Pattern Recognition — 20 citations into it
• Generative Models — 17 citations into it
• Computational Mechanics — 14 citations into it; #8,450 of 10,001 by trust here, #7,173 by citations
• Privacy & Security — 13 citations into it
• Safety, Robustness & Interpretability — 10 citations into it
• Optimization & Training — 9 citations into it
• Representation & Self-Supervised Learning — 6 citations into it

Whom Liyang Xie trusts overall

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

1. Cynthia Dwork
2. Kamalika Chaudhuri
3. Jianhui Chen
4. Paul Tseng
5. Abhradeep Thakurta
6. Nhathai Phan
7. Richard Baraniuk
8. Jieping Ye
9. Adam D. Smith
10. Geoffrey E. Hinton

Who trusts Liyang Xie overall

1. Sergey I. Nikolenko
2. Aleksei Triastcyn
3. Yu Zhang
4. James Jordon
5. Reihaneh Torkzadehmahani
6. Yang Wang
7. Ahmed M. Alaa
8. Ying-Cheng Lu
9. Dingfan Chen
10. Lorenzo Frigerio

Papers from Liyang Xie's perspective

Ordered by how strongly the researchers Liyang Xie 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. Gradient-based learning applied to document recognition
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. ImageNet: A large-scale hierarchical image database
6. Learning Multiple Layers of Features from Tiny Images
7. Long Short-Term Memory
8. Attention is All you Need (Neural Information Processing Systems)
9. GENERATIVE ADVERSARIAL NETS
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Differentially Private Generative Adversarial Network (2018) — 593 citations
• Privacy-Preserving Distributed Multi-Task Learning with Asynchronous Updates (2017) — 77 citations