Zhenguang Liu
Artificial Intelligence · 2017–2021
A researcher in the Science corpus: 5 papers; trusts 31 researchers and is trusted by 2 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 98 citations into it; #35,040 of 35,345 by trust here, #20,377 by citations
- Information Systems — 88 citations into it; #7,681 of 8,771 by trust here, #3,761 by citations
- Computer Vision and Pattern Recognition — 33 citations into it
- Signal Processing — 24 citations into it
- Graph Learning — 20 citations into it
- Management Science and Operations Research — 16 citations into it
- Representation & Self-Supervised Learning — 11 citations into it
- Optimization & Training — 7 citations into it
Whom Zhenguang Liu trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Yoshua Bengio
- Thomas Kipf
- Xavier Glorot
- Geoffrey E. Hinton
- Diederik P. Kingma
- Max Welling
- Xiangnan He
- Bo Jiang
- Alex Krizhevsky
- David G. Lowe
Who trusts Zhenguang Liu overall
Papers from Zhenguang Liu's perspective
Ordered by how strongly the researchers Zhenguang Liu trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- Learning Multiple Layers of Features from Tiny Images
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
Their papers
- NAIS: Neural Attentive Item Similarity Model for Recommendation (2018) — 531 citations
- Fusion of Magnetic and Visual Sensors for Indoor Localization: Infrastructure-Free and More Effective (2017) — 114 citations
- Combining Graph Neural Networks With Expert Knowledge for Smart Contract Vulnerability Detection (2021) — 329 citations
- Learning Intents behind Interactions with Knowledge Graph for Recommendation (2021) — 609 citations
- Smart Contract Vulnerability Detection using Graph Neural Network (2020) — 440 citations