5 papers
Adaptive Spatio-temporal Estimation on the Graph Edges via Line Graph Transformation
Yi Yan, Ercan Engin Kuruoglu
Spatial-temporal estimation of signals on graph edges is challenging because most conventional Graph Signal Processing techniques are defined on the graph nodes. Leveraging the Lin…
Signal Processing over Time-Varying Graphs: A Systematic Review
Yi Yan, Jiacheng Hou, Zhenjie Song +1
As irregularly structured data representations, graphs have received a large amount of attention in recent years and have been widely applied to various real-world scenarios such a…
LLM Online Spatial-temporal Signal Reconstruction Under Noise
Yi Yan, Dayu Qin, Ercan Engin Kuruoglu
This work introduces the LLM Online Spatial-temporal Reconstruction (LLM-OSR) framework, which integrates Graph Signal Processing (GSP) and Large Language Models (LLMs) for online…
Graph Signal Adaptive Message Passing
Yi Yan, Changran Peng, Ercan Engin Kuruoglu
This paper proposes Graph Signal Adaptive Message Passing (GSAMP), a novel message passing method that simultaneously conducts online prediction, missing data imputation, and noise…
Time-varying Graph Signal Estimation via Dynamic Multi-hop Topologies
Yi Yan, Fengfan Zhao, Ercan Engin Kuruoglu
The assumption of using a static graph to represent multivariate time-varying signals oversimplifies the complexity of modeling their interactions over time. We propose a Dynamic M…