232 citations · 1.4k across the 72 of their papers we have counts for
9 papers · 1 filter
Measuring and Sampling: A Metric-guided Subgraph Learning Framework for Graph Neural Network
Jiyang Bai, Yuxiang Ren, Jiawei Zhang
Graph neural network (GNN) has shown convincing performance in learning powerful node representations that preserve both node attributes and graph structural information. However,…
Translational Concept Embedding for Generalized Compositional Zero-shot Learning
He Huang, Wei Tang, Jiawei Zhang +1
Generalized compositional zero-shot learning means to learn composed concepts of attribute-object pairs in a zero-shot fashion, where a model is trained on a set of seen concepts a…
A Self-supervised Mixed-curvature Graph Neural Network
Li Sun, Zhongbao Zhang, Junda Ye +4
Graph representation learning received increasing attentions in recent years. Most of existing methods ignore the complexity of the graph structures and restrict graphs in a single…
Continuous-Time Sequential Recommendation with Temporal Graph Collaborative Transformer
Ziwei Fan, Zhiwei Liu, Jiawei Zhang +3
In order to model the evolution of user preference, we should learn user/item embeddings based on time-ordered item purchasing sequences, which is defined as Sequential Recommendat…
Learning RAW-to-sRGB Mappings with Inaccurately Aligned Supervision
Zhilu Zhang, Haolin Wang, Ming Liu +3
Learning RAW-to-sRGB mapping has drawn increasing attention in recent years, wherein an input raw image is trained to imitate the target sRGB image captured by another camera. Howe…
Centrality Meets Centroid: A Graph-based Approach for Unsupervised Document Summarization
Haopeng Zhang, Jiawei Zhang
Unsupervised document summarization has re-acquired lots of attention in recent years thanks to its simplicity and data independence. In this paper, we propose a graph-based unsupe…
Hyperbolic Variational Graph Neural Network for Modeling Dynamic Graphs
Li Sun, Zhongbao Zhang, Jiawei Zhang +4
Learning representations for graphs plays a critical role in a wide spectrum of downstream applications. In this paper, we summarize the limitations of the prior works in three fol…
Adversarial Active Learning based Heterogeneous Graph Neural Network for Fake News Detection
Yuxiang Ren, Bo Wang, Jiawei Zhang +1
The explosive growth of fake news along with destructive effects on politics, economy, and public safety has increased the demand for fake news detection. Fake news on social media…
Label Contrastive Coding based Graph Neural Network for Graph Classification
Yuxiang Ren, Jiyang Bai, Jiawei Zhang
Graph classification is a critical research problem in many applications from different domains. In order to learn a graph classification model, the most widely used supervision co…