Liang Chen

Artificial Intelligence · with Xie · 2018–2020

A researcher in the Science corpus: 3 papers; trusts 116 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 87 citations into it
• Computer Vision and Pattern Recognition — 43 citations into it
• Representation & Self-Supervised Learning — 36 citations into it; #2,319 of 3,145 by trust here, #1,982 by citations
• Information Systems — 27 citations into it
• Graph Learning — 15 citations into it
• Generative Models — 10 citations into it
• Statistical and Nonlinear Physics — 7 citations into it
• Molecular Biology — 6 citations into it

Whom Liang Chen trusts overall

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

1. Alex Krizhevsky
2. Geoffrey E. Hinton
3. Yoshua Bengio
4. Yann LeCun
5. Ilya Sutskever
6. Diederik P. Kingma
7. Kaiming He
8. Mingsheng Long
9. L. Eon Bottou
10. Ross B. Girshick

Who trusts Liang Chen overall

1. Umberto Michieli
2. Hyeonseob Nam

Papers from Liang Chen's perspective

Ordered by how strongly the researchers Liang Chen 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. Gradient-based learning applied to document recognition
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. GENERATIVE ADVERSARIAL NETS
9. Learning Multiple Layers of Features from Tiny Images
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Secure Deep Graph Generation with Link Differential Privacy (2020) — 52 citations
• Self-supervised Graph Learning for Recommendation (2020) — 1,757 citations
• Learning Semantic Representations for Unsupervised Domain Adaptation (2018) — 535 citations