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A Hilbert Space Theory of Generalized Graph Signal Processing

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Outgoing claims: the papers this work cites, builds on, or argues with.

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A Course in Functional Analysis
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Finding an infection source under the SIS model
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Network topology inference from non-stationary graph signals
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Graph Learning From Data Under Laplacian and Structural Constraints
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Kernel-based Reconstruction of Space-time Functions on Dynamic Graphs
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Estimating Infection Sources in Networks Using Partial Timestamps
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Rumors in a Network: Who's the Culprit?
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Information Source Detection in the SIR Model: A Sample-Path-Based Approach
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Discrete Signal Processing on Graphs
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Identifying Infection Sources and Regions in Large Networks
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Learning Laplacian Matrix in Smooth Graph Signal Representations
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An Algorithmic Framework for Estimating Rumor Sources With Different Start Times
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Filtering Random Graph Processes Over Random Time-Varying Graphs
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A Time-Vertex Signal Processing Framework: Scalable Processing and Meaningful Representations for Time-Series on Graphs
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Irregularity-Aware Graph Fourier Transforms
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Adaptive-network models of collective dynamics
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Active semi-supervised learning using sampling theory for graph signals
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Geometric Signal Processing on Polygonal Meshes
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Learning Correlation Graph and Anomalous Employee Behavior for Insider Threat Detection
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Enhancing Time Synchronization Support in Wireless Sensor Networks
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Introduction to Hilbert spaces with applications

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Generalized sampling of multi-dimensional graph signals based on prior information
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Discrete linear canonical transform on graphs: Uncertainty principle and sampling
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Sampling of graph signals based on joint time-vertex fractional Fourier transform
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Signal Processing on Simplicial Complexes With Vertex Signals
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Distance-Based Laplacian Algebra for Effective Subgraph Filter Learning
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Wide-Sense Stationarity and Spectral Estimation for Generalized Graph Signal
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Time-Varying Signals Recovery Via Graph Neural Networks
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Kernel Ridge Regression for Generalized Graph Signal Processing
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A Generalized Graph Signal Processing Framework for Multiple Hypothesis Testing over Networks
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Spectral Convergence of Simplicial Complex Signals
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Robust Recovery for Graph Signal via $\ell _{0}$-Norm Regularization
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Multiway Graph Signal Processing on Tensors: Integrative Analysis of Irregular Geometries
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Graph Distributional Signals for Regularization in Graph Neural Networks
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Subset Random Sampling and Reconstruction of Finite Time-Vertex Graph Signals
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Wide-Sense Stationarity in Generalized Graph Signal Processing
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Graph Signal Processing Over a Probability Space of Shift Operators
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Kernel Based Reconstruction for Generalized Graph Signal Processing
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Modeling Sparse Graph Sequences and Signals Using Generalized Graphons
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Fault Diagnosis of Rolling Bearing Based on Variational Mode Decomposition and Improved Canberra Distance in Symmetrized Dot Pattern Image
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