3 papers
eess.SP2025
Subset Random Sampling and Reconstruction of Finite Time-Vertex Graph Signals
Hang Sheng, Qinji Shu, Hui Feng +1
Finite time-vertex graph signals (FTVGS) provide an efficient representation for capturing spatio-temporal correlations across multiple data sources on irregular structures. Althou…
eess.SP2024
Subset Random Sampling of Finite Time-vertex Graph Signals
Hang Sheng, Qinji Shu, Hui Feng +1
Time-varying data with irregular structures can be described by finite time-vertex graph signals (FTVGS), which represent potential temporal and spatial relationships among multipl…
cs.LG2024
The Transferability of Downsamped Sparse Graph Convolutional Networks
Qinji Shu, Hang Sheng, Feng Ji +2
To accelerate the training of graph convolutional networks (GCNs) on real-world large-scale sparse graphs, downsampling methods are commonly employed as a preprocessing step. Howev…