252 citations · 404 across the 5 of their papers we have counts for
5 papers
Variational Graph Generator for Multi-View Graph Clustering
Jianpeng Chen, Yawen Ling, Jie Xu +6
Multi-view graph clustering (MGC) methods are increasingly being studied due to the explosion of multi-view data with graph structural information. The critical point of MGC is to…
Learning from Atypical Behavior: Temporary Interest Aware Recommendation Based on Reinforcement Learning
Ziwen Du, Ning Yang, Zhonghua Yu +1
Traditional robust recommendation methods view atypical user-item interactions as noise and aim to reduce their impact with some kind of noise filtering technique, which often suff…
FedGraphNN: A Federated Learning System and Benchmark for Graph Neural Networks
Chaoyang He, Keshav Balasubramanian, Emir Ceyani +11
Graph Neural Network (GNN) research is rapidly growing thanks to the capacity of GNNs in learning distributed representations from graph-structured data. However, centralizing a ma…
Self-Supervised Discriminative Feature Learning for Deep Multi-View Clustering
Jie Xu, Yazhou Ren, Huayi Tang +6
Multi-view clustering is an important research topic due to its capability to utilize complementary information from multiple views. However, there are few methods to consider the…
Graph Convolutional Neural Networks based on Quantum Vertex Saliency
Lu Bai, Yuhang Jiao, Luca Rossi +3
This paper proposes a new Quantum Spatial Graph Convolutional Neural Network (QSGCNN) model that can directly learn a classification function for graphs of arbitrary sizes. Unlike…