activity
20192025
most citedIntroducing Hypergraph Signal Processing: Theoretical Foundation and Practical Applications

74 citations · 159 across the 12 of their papers we have counts for

collaborators

12 papers

cs.LG2025★ 1 cited

Mixture-of-Experts for Distributed Edge Computing with Channel-Aware Gating Function

Qiuchen Song, Shusen Jing, Shuai Zhang +2

In a distributed mixture-of-experts (MoE) system, a server collaborates with multiple specialized expert clients to perform inference. The server extracts features from input data…

eess.SP2023★ 1 cited

Radiomap Inpainting for Restricted Areas based on Propagation Priority and Depth Map

Songyang Zhang, Tianhang Yu, Brian Choi +2

Providing rich and useful information regarding spectrum activities and propagation channels, radiomaps characterize the detailed distribution of power spectral density (PSD) and a…

eess.SP2022★ 3 cited

RME-GAN: A Learning Framework for Radio Map Estimation based on Conditional Generative Adversarial Network

Songyang Zhang, Achintha Wijesinghe, Zhi Ding

Outdoor radio map estimation is an important tool for network planning and resource management in modern Internet of Things (IoT) and cellular systems. Radio map describes spatial…

eess.SP2022

Exemplar-Based Radio Map Reconstruction of Missing Areas Using Propagation Priority

Songyang Zhang, Tianhang Yu, Jonathan Tivald +3

Radio map describes network coverage and is a practically important tool for network planning in modern wireless systems. Generally, radio strength measurements are collected to co…

cs.CV2021★ 1 cited

Hyperspectral Image Segmentation based on Graph Processing over Multilayer Networks

Songyang Zhang, Qinwen Deng, Zhi Ding

Hyperspectral imaging is an important sensing technology with broad applications and impact in areas including environmental science, weather, and geo/space exploration. One import…

eess.SP2021★ 2 cited

Image Processing via Multilayer Graph Spectra

Songyang Zhang, Qinwen Deng, Zhi Ding

Graph signal processing (GSP) has become an important tool in image processing because of its ability to reveal underlying data structures. Many real-life multimedia datasets, howe…

eess.SP2021★ 1 cited

Signal Processing over Multilayer Graphs: Theoretical Foundations and Practical Applications

Songyang Zhang, Qinwen Deng, Zhi Ding

Signal processing over single-layer graphs has become a mainstream tool owing to its power in revealing obscure underlying structures within data signals. However, many real-life d…

eess.SP2021★ 8 cited

Point Cloud Resampling Through Hypergraph Signal Processing

Qinwen Deng, Songyang Zhang, Zhi Ding

Three-dimensional (3D) point clouds are important data representations in visualization applications. The rapidly growing utility and popularity of point cloud processing strongly…

eess.SP2020★ 2 cited

From Spectrum Wavelet to Vertex Propagation: Graph Convolutional Networks Based on Taylor Approximation

Songyang Zhang, Han Zhang, Shuguang Cui +1

Graph convolutional networks (GCN) have been recently utilized to extract the underlying structures of datasets with some labeled data and high-dimensional features. Existing GCNs…

eess.SP2020★ 63 cited

Hypergraph Spectral Analysis and Processing in 3D Point Cloud

Songyang Zhang, Shuguang Cui, Zhi Ding

Along with increasingly popular virtual reality applications, the three-dimensional (3D) point cloud has become a fundamental data structure to characterize 3D objects and surround…

eess.SP2020★ 3 cited

Point Cloud Segmentation based on Hypergraph Spectral Clustering

Songyang Zhang, Shuguang Cui, Zhi Ding

Hypergraph spectral analysis has emerged as an effective tool processing complex data structures in data analysis. The surface of a three-dimensional (3D) point cloud and the multi…

eess.SP2019★ 74 cited

Introducing Hypergraph Signal Processing: Theoretical Foundation and Practical Applications

Songyang Zhang, Zhi Ding, Shuguang Cui

Signal processing over graphs has recently attracted significant attentions for dealing with structured data. Normal graphs, however, only model pairwise relationships between node…