78 citations · 265 across the 23 of their papers we have counts for
23 papers
Network Tomography with Path-Centric Graph Neural Network
Yuntong Hu, Junxiang Wang, Liang Zhao
Network tomography is a crucial problem in network monitoring, where the observable path performance metric values are used to infer the unobserved ones, making it essential for ta…
GraphSL: An Open-Source Library for Graph Source Localization Approaches and Benchmark Datasets
Junxiang Wang, Liang Zhao
We introduce GraphSL, a new library for studying the graph source localization problem. graph diffusion and graph source localization are inverse problems in nature: graph diffusio…
Non-Euclidean Spatial Graph Neural Network
Zheng Zhang, Sirui Li, Jingcheng Zhou +4
Spatial networks are networks whose graph topology is constrained by their embedded spatial space. Understanding the coupled spatial-graph properties is crucial for extracting powe…
POND: Multi-Source Time Series Domain Adaptation with Information-Aware Prompt Tuning
Junxiang Wang, Guangji Bai, Wei Cheng +3
Time series domain adaptation stands as a pivotal and intricate challenge with diverse applications, including but not limited to human activity recognition, sleep stage classifica…
Curriculum Learning for Graph Neural Networks: Which Edges Should We Learn First
Zheng Zhang, Junxiang Wang, Liang Zhao
Graph Neural Networks (GNNs) have achieved great success in representing data with dependencies by recursively propagating and aggregating messages along the edges. However, edges…
Deep Graph Representation Learning and Optimization for Influence Maximization
Chen Ling, Junji Jiang, Junxiang Wang +5
Influence maximization (IM) is formulated as selecting a set of initial users from a social network to maximize the expected number of influenced users. Researchers have made great…