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Stochastic Block Model
The stochastic block model is a statistical problem where the goal is to recover a community structure from a graph. The model is defined by a graph G with vertex set [n] =... -
DESIGN OF SAMPLING SET FOR BANDLIMITED GRAPH SIGNAL ESTIMATION
The dataset used in the paper is a graph signal dataset, which is a graph signal defined over a graph. The dataset is used to test the proposed algorithm for sampling set design... -
Blind Demixing of Diffused Graph Signals
Blind demixing of diffused graph signals, an extension of blind demixing of time (or spatial) domain signals to graphs. -
GraphBGS: Background Subtraction via Recovery of Graph Signals
Background subtraction is a fundamental pre-processing task in computer vision. This task becomes challenging in real scenarios due to variations in the background for both... -
Diffusion Networks
The dataset used in the paper is a graph signal processing dataset, where the goal is to estimate a parameter vector of interest using a distributed adaptive network. -
Signal-adapted tight frames on graphs
Signal-adapted tight frames on graphs -
Gaussian Processes on Graphs via Spectral Kernel Learning
Gaussian Processes on Graphs via Spectral Kernel Learning -
Real-World Graph Dataset
The dataset used in the paper is a real-world graph dataset, where the goal is to recover signal values on test nodes. -
Synthetic Graph Dataset
A synthetic dataset of 200 graphs with 5 nodes each, where nodes were randomly placed within a designated area of operation using a random point configuration of the Euclidean... -
Graph Signal Regression Task
The dataset used in the paper is a graph signal regression task, where the goal is to recover signal values on test nodes.
