Zhiwei Liu

Artificial Intelligence · International Conference on Information and Knowledge Management · 2020–2022

A researcher in the Science corpus: 3 papers; trusts 18 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 50 citations into it
• Information Systems — 26 citations into it
• Computer Vision and Pattern Recognition — 16 citations into it
• Representation & Self-Supervised Learning — 16 citations into it
• Management Science and Operations Research — 9 citations into it
• Graph Learning — 8 citations into it
• Computer Networks and Communications — 6 citations into it

Whom Zhiwei Liu trusts overall

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

1. Thomas Kipf
2. Shebuti Rayana
3. Diederik P. Kingma
4. Geoffrey E. Hinton
5. Max Welling
6. Kaiming He
7. Yoshua Bengio
8. Steffen Rendle
9. William L. Hamilton
10. Julian McAuley

Who trusts Zhiwei Liu overall

1. Jianheng Tang
2. Xiaoxiao Ma
3. Yingtong Dou
4. Jiajin Li
5. Yang Liu
6. Zi-Chao Gao

Papers from Zhiwei Liu's perspective

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

Their papers

• Intent Contrastive Learning for Sequential Recommendation (2022) — 463 citations
• Enhancing Graph Neural Network-based Fraud Detectors against Camouflaged Fraudsters (2020) — 744 citations
• Alleviating the Inconsistency Problem of Applying Graph Neural Network to Fraud Detection (2020) — 383 citations