Overview

Graph Signal Processing treats measurements attached to connected entities—such as sensors, brain regions, or traffic locations—as signals whose structure follows a graph, enabling analysis beyond regular grids. Common tools include graph Laplacians and graph Fourier transforms, spectral and polynomial filters, wavelets, sampling and compressed sensing, and learned graph structures. Current work extends these tools to time-varying and directed graphs, hypergraphs, and sheaves, with applications including denoising, interpolation, anomaly detection, recommendation, and generative modeling. A central tension is that smoothness makes signals easier to estimate and compress but can erase high-frequency or heterophilous structure; methods must also balance robustness to graph errors with fidelity and scalability.

Latest papers

CardsList

35 papers5 papers in the last four weeks, up 25% on the four weeks before. 0.0% of all new papers.

  1. Stabilizing Filters for Graph Signal Generation

    Oct 20, 2026Martin Schmidt, Gonzalo MateosGraph Signal ProcessingNeural Network Stability

  2. Graph Residual Conjugate Diffusion: SNR-Equalized Heat Flow for Graph Signals

    Sep 30, 2026Jinwei Li, Daniel TenbrinckGraph Signal ProcessingDiffusion Model Inference Acceleration

  3. Hierarchical Clustering and Signal Denoising on Digraphs

    Sep 28, 2026Yi Wang, Sippanon Kitimoon, Hrushikesh N. Mhaskar +1Graph Signal ProcessingHierarchical Clustering

  4. TwinS-GCN: Spectral conjugate for Spectral Graph Convolutional Networks

    Sep 26, 2026Chun Hei Michael Chan, Flavia Petruso, Dimitri Van De VilleGraph Neural NetworksSpectral Graph Convolution

  5. Graph Learning with Spectral Connectivity Priors for Scarce Data

    Sep 23, 2026Mingxiao Liu, Bahar Oveisgharan, Bingyan Zou +3Graph Signal ProcessingGraph Structure Learning

  6. Topological Signal Processing With Unoriented Operators

    Sep 21, 2026Andrea Cavallo, Varun Sarathchandran, Geert Leus +1Graph Signal ProcessingSpectral Methods

  7. Stable Filters for Generative Modeling of Graph Signals

    Sep 16, 2026Martin Schmidt, Gonzalo MateosGraph Signal ProcessingAlgorithmic Stability

  8. Feature Transformation Enhanced Jacobi Polynomial Graph Filtering for Graph Anomaly Detection

    Aug 27, 2026Xiang Wang, Zhijun Cheng, Zhenyu MengAnomaly DetectionGraph Neural Networks

  9. Sheaf-theoretic Signal Processing on Graphs: Spectral Theory, Filtering, and Sampling

    Aug 2, 2026Gabriele D'Acunto, Leonardo Di Nino, Paolo Di Lorenzo +1Graph Signal ProcessingSheaf Theory

  10. Does Graph Compression Preserve Signal Propagation?

    Jul 25, 2026Kawshik Banerjee, Khaled Mohammed SaifuddinGraph Signal ProcessingGraph Coarsening

  11. Multilevel Graph Wavelet Compressed Sensing with Scale-Aware Neural Recovery

    Jul 23, 2026Amirhossein Nouranizadeh, Sarang Rajendra Patil, Alan John Varghese +3Graph Signal ProcessingSparse Recovery

  12. Tonnetz-Driven Graph Wedgelet for Harmonic Complexity Reduction in Music Scores

    Jul 9, 2026Emmanuel Caronna, Elisa Francomano, Silvia LicciardiGraph Signal Processing

  13. Stability of Flow Models for Graph Signals

    Jul 8, 2026Martin Schmidt, Gonzalo MateosGraph Signal ProcessingFlow Matching

  14. Directed Graph Topology Inference via Graph Filter Identification

    Jun 25, 2026Rasoul Shafipour, Andrei Buciulea, Santiago Segarra +2Graph Signal ProcessingGraph Structure Learning

  15. A Framework for Directed Hypergraph Signal Processing via tensor t-SVD

    Jun 23, 2026Carlos Mundo-Levano, Nicolás Bello, Daniel L. Lau +1Graph Signal Processing

  16. Low-rank Updates in Slowly Time-varying Graphs for Spatial-Temporal Signal Interpolation

    Jun 22, 2026Saghar Bagheri, Gene Cheung, Tim Eadie +1Graph Signal ProcessingGraph Structure Learning

  17. Statistical Testing on Directed Graphs by Surrogate Data Generation

    May 30, 2026Chun Hei Michael Chan, Alexandre Cionca, Dimitri Van De VilleGraph Signal ProcessingSynthetic Data Generation

  18. DDGAD: Disagreement-Driven Graph Anomaly Detection via Adapt-Then-Combine

    May 26, 2026Yuxin Yang, Limei Hu, Feng ChenGraph Signal ProcessingUnsupervised Anomaly Detection

  19. Spectral bandits for smooth graph functions with applications in recommender systems

    May 19, 2026Tomáš Kocák, Michal Valko, Rémi Munos +2Graph Signal ProcessingMulti-Armed Bandits

  20. Graph Neural Networks for Community Detection in Graph Signal Analysis

    May 19, 2026Roberto Cavoretto, Alessandra De Rossi, Enrico MontiniGraph Signal Processing

  21. GOMA: Toward Structure-Driven Multimodal Alignment from a Graph Signal Smoothing Perspective

    May 15, 2026Xu Wang, Xunkai Li, Yinlin Zhu +2Cross-Modal LearningMultimodal IR

  22. Triple Spectral Fusion for Sensor-based Human Activity Recognition

    May 4, 2026Ye Zhang, Longguang Wang, Qing Gao +3Graph Signal ProcessingHuman Activity Recognition

  23. Operational Feature Fingerprints of Graph Datasets via a White-Box Signal-Subspace Probe

    Apr 24, 2026Yuchen Xiong, Swee Keong Yeap, Zhen Hong BanGraph Signal ProcessingNode Classification

  24. Spectral bandits for smooth graph functions

    Apr 20, 2026Michal Valko, Rémi Munos, Branislav Kveton +1Graph Signal ProcessingMulti-Armed Bandits

  25. Learning Superpixel Ensemble and Hierarchy Graphs for Melanoma Detection

    Apr 4, 2026Asmaa M. Elwer, Muhammad A. Rushdi, Mahmoud H. AnnabySkin Lesion ClassificationMedical Image Classification

  26. GSNR: Graph Smooth Null-Space Representation for Inverse Problems

    Feb 23, 2026Romario Gualdrón-Hurtado, Roman Jacome, Rafael S. Suarez +1Inverse ProblemsImage Inverse Problems