Shangqing Liu

Artificial Intelligence · 2019–2020

A researcher in the Science corpus: 2 papers; trusts 1 researcher and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 30 citations into it
• Graph Learning — 6 citations into it

Whom Shangqing Liu trusts overall

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

1. Jasper Snoek
2. Miltiadis Allamanis
3. Hanjun Dai
4. Geoffrey E. Hinton
5. Yujia Li
6. Yoshua Bengio
7. Muhan Zhang
8. Fabian Yamaguchi

Who trusts Shangqing Liu overall

1. Yi Li
2. Michael Fu
3. Yichen Xu
4. Saikat Chakraborty
5. Guru Prasad Bhandari
6. Yue Wang

Papers from Shangqing Liu's perspective

Ordered by how strongly the researchers Shangqing 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. Long Short-Term Memory
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. Learning Multiple Layers of Features from Tiny Images
8. ImageNet: A large-scale hierarchical image database
9. Going deeper with convolutions
10. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)

Their papers

• AbdomenCT-1K: Is Abdominal Organ Segmentation a Solved Problem? (2020) — 479 citations
• Devign: Effective Vulnerability Identification by Learning Comprehensive Program Semantics via Graph Neural Networks (2019) — 1,186 citations