Graph Signal Processing

A) Sampling Signal Techniques (21  papers) 

D. Wei, Z. Yan, “Generalized Sampling of Multi-dimensional Graph Signals based on Prior Information”, Signal Processing, 2024.

W. Liu, H. Feng, F. Ji, B. Hu, "Online Signed Sampling of Bandlimited Graph Signals",  IEEE Transactions on Signal and Information Processing over Networks, Volume 10, pages 131-146, 2024 .

G. Yang, Q. Zhang, L. Yang, "Piecewise-Constant Representation and Sampling of Bandlimited Signals on Graphs", IEEE Transactions on Signal and Information Processing over Networks,  Volume 10, pages 332-346, 2024.

K. Yanagiya, H. Higashi, Y. Tanaka, “Edge Sampling based on Graph Sampling Theory for Graph Sparsification”, IEICE Proceedings Series, 2024.

J. Miettinen, S. Vorobyov, E. Ollila, X. Wang, "Correlation-based Graph Smoothness Measures in Graph Signal Processing", European Signal Processing Conference, EUSIPCO 2023, Helsinki, Finland, 2023.

B. Sripathmanathan, X. Dong, M. Bronstein, "On the Impact of Sample Size in Reconstructing Graph Signals", International Conference on Sampling Theory and Applications, SampTA 2023, pages 1-6, New Haven, USA, 2023.

J. Hara, Y. Tanaka, Y. Eldar, "Graph Signal Sampling under Stochastic Priors", IEEE Transactions on Signal Processing, Volume 71, paages 1421-1434, 2023, 

J. Hara, Y. Tanaka, "Multi-Channel Sampling on Graphs and Its Relationship to Graph Filter Banks", IEEE Open Journal of Signal Processing, Volume 4, pages 148-156, 2023.

Q. Yao, L. Huang, S. Tang, "Space-Time Variable Density Samplings for Sparse Bandlimited Graph Signals Driven by Diffusion Operators", IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023, Rhodes Island, Greece, 2023.

F. Wang, T. Li, X. Zhang, "Revisit Sampling Theory of Bandlimited Graph Signals: One Bridge Between GSP and DSP", IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023, Rhodes Island, Greece, 2023.

Y. Li, H. Zhao, G. Cheung, "Eigen-Decomposition-Free Directed Graph Sampling via Gershgorin Disc Alignment", IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023, Rhodes Island, Greece, 2023.

J. Shi, J. M. Moura, "Graph Signal Processing: Dualizing GSP Sampling in the Vertex and Spectral Domains", IEEE Transactions on Signal Processing,  May 2022.

Y. Kim, “Quantization-aware sampling set selection for bandlimited graph signals”, EURASIP Journal on Advances in Signal Processing, January 2022.

Y. Tanaka, Y. C. Eldar, A. Ortega, G. Cheung, "Sampling Signals on Graphs: From Theory to Applications", IEEE Signal Processing Magazine, Volume 37, No. 6, pages 14-30, November 2020.

Y. Tanaka, "Spectral Domain Sampling of Graph Signals", IEEE Transactions on Signal Processing, Volume 66 , pages 3752-3767, 2018.

Y. Tanaka, Y. Eldar, "Generalized Sampling on Graphs with a Subspace Prior", International conference on Sampling Theory and Applications, SampTA 2019, pages 1-4, 2019.

Y. Tanaka, Y. Eldar, "Generalized Sampling on Graphs with Subspace and Smoothness Priors", IEEE Transactions on Signal Processing, Volume 68 , pages 2272-2286, 2020.

S. Chepuri, Y. Eldar, G. Leus, "Graph Sampling with and without Input Priors", IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2018, pages 4564-4568, 2018.

D. Valsesia, G. Fracastoro, E. Magli, "Sampling of Graph Signals via Randomized Local Aggregations", IEEE Transactions on Signal and Information Processing over Networks, Volume 5 , pages 348-359, 2018.

R. Varma, J. Kovacevic, "Sampling Theory for Graph Signals on Product Graphs", IEEE Global Conference on Signal and Information Processing, GlobalSIP 2018,  pages 768-772, 2018.

L. Chamon, A. Ribeiro, “Greedy Sampling of Graph Signals", IEEE Transactions on Signal Processing, Volume 66, No. 1, pages 34-47, 2017.

B) Recovery Techniques (18 papers)

B.1) Recovering in the General Case (12 papers)

W. Liu, H. Feng, K. Wang, F. Ji, B. Hu, "Recovery of Graph Signals from Sign Measurements", Preprint, September 2021.

E. Simou, P. Frossard, “Graph Signal Representation with Wasserstein Barycenters", IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2019, pages 5386–5390, 2019.

S. Foucart, C. Liao, N. Veldt, "On the Optimal Recovery of Graph Signals", International Conference on Sampling Theory and Applications, SampTA 2023, New Haven, USA, 2023.

A. Sadigh, H. Zayyani, M. Korki, "A Robust Proportionate Graph Recursive Least Squares Algorithm for Adaptive Graph Signal Recovery”, IEEE Transactions on Circuits and Systems, 2024.

A. Fascista, A. Coluccia, C. Ravazzi, "Graph Signal Reconstruction under Heterogeneous Noise via Adaptive Uncertainty-Aware Sampling and Soft Classification”, IEEE Transactions on Signal and Information Processing over Networks, 2024.

F. Chen, G. Cheung, X. Zhang, "Manifold Graph Signal Restoration suing Gradient Graph Laplacian Regularizer",  IEEE Transactions on Signal Processing, Volume 72, pages 744-761, 2024.

R. Torkamani, A. Amini, H. Zayyani, M. Korki, "Graph Signal Recovery using Variational Bayes in Fourier Pairs with Cramér–Rao bounds", Signal Processing, Volume 219, 2024.

A. Sadigh, H. Zayyani, M. Korki, "A Robust Proportionate Graph Recursive Least Squares Algorithm for Adaptive Graph Signal Recovery", IEEE Transactions on Circuits and Systems II: Express Briefs, 2024.

Y. Yan, C. Peng, E. Kuruoglu, “Adaptive Least Mean Squares Graph Neural Networks and Online Graph Signal Estimation”, January 2024.

H. Zhao, C. Li, W. Xiang, "Data-Reuse Adaptive Algorithms for Graph Signal Estimation over Sensor Network”, IEEE Sensors Journal, Volume 24, No. 4, pages 5086-5096, February 2024.

I. Zach, T. Dvorkind, R. Talmon, “Graph signal interpolation and extrapolation over manifold of Gaussian mixture”, Signal Processing, March 2024.

A. Fascista, A. Coluccia, C. Ravazzi, "Graph Signal Reconstruction under Heterogeneous Noise via Adaptive Uncertainty-Aware Sampling and Soft Classification”, IEEE Transactions on Signal and Information Processing over Networks, Volume 10, pages 277-293, 2024/

B.2) Recovering from Noisy or Incomplete Observations (6 papers)

Z. Liu, F. Chen, S. Duan, "Distributed Subspace Projection Graph Signal Estimation with Anomaly Interference", IEEE Transactions on Network Science and Engineering, May 2023.

Y. He, H. Wai, "Central Nodes Detection from Partially Observed Graph Signals", IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023, Rhodes Island, Greece, 2023. 

A. Jayawant, A. Ortega, "Towards Bandwidth Estimation for Graph Signal Reconstruction", IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023, Rhodes Island, Greece, 2023.

A. Javaheri, A. Amini, F. Marvasti, D. Palomar, "Joint Signal Recovery and Graph Learning from Incomplete Time-Series”, IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2024, Seoul, South Korea, pages 13511-13515, 2024.

Y. Cao, X. Jiang, J. Wang, S. Zhou, X. Hou, "An efficient algorithm with fast convergence rate for sparse graph signal reconstruction", EURASIP Journal on Advances in Signal Processing, March 2024.

E. Antonian, G. Peters, M. Chantler, "Bayesian reconstruction of Cartesian product graph signals with general patterns of missing data", Journal of the Franklin Institute, April 2024.

C) Time Varying Graphs (37 papers)

V. Kalofolias, A. Loukas, D. Thanou, P. Frossard, “Learning time varying graphs", IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2017, pages 2826–2830, 2017.

K. Qiu, X. Mao, X. Shen, X. Wang, T. Li, Y. Gu, “Time-varying graph signal reconstruction", IEEE Journal of Selected Topics in Signal Processing, Volume 11, No. 6, pages 870–883, 2017.

Y. Liu, L. Yang, K. You, W. Guo, W. Wang, "Graph Learning based on Spatiotemporal Smoothness for Time-Varying Graph Signal", IEEE Access, Volume 7, pages 62372-62386, 2019.

K. Yamada, Y. Tanaka, A. Ortega, "Time-varying Graph Learning based on Sparseness of Temporal Variation', IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2019, Brighton, UK, pages 5411-5415, 2019.

K. Yamada, Y. Tanaka, A. Ortega, “Time-varying graph learning with constraints on graph temporal variation," Preprint, 2020.

J. Jiang, D. Tay, Q. Sun, S. Ouyang, “Recovery of time-varying graph signals via distributed algorithms on regularized problems", IEEE Transactions on Signal and Information Processing over Networks, Volume 6, pages 540–555, 2020.

Z. Qi, G. Li, S. Zhai,G. Zhang, "Incremental Data-Driven Topology Learning for Time-Varying Graph Signals", IEEE Global Communications Conference, pages 1-6, Taipei, Taiwan, 2020.

S. Chen, Y. Eldar, "Time-Varying Graph Signal Inpainting via Unrolling Networks", IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2021,Toronto, Canada, 2021.

S. Sardellitti, S. Barbarossa, P. Lorenzo, "Online Learning of Time-Varying Signals and Graphs", IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2021, Toronto, Canada, pages 5230-5234, 2021.

B. Si, D. Luo, J. Zhu, "Online Graph Learning for Time-Varying Graphs", IET Electronics Letters, December 2021.

W. Liu, H. Yan, Q. Wang, N. Hu, N. Liu, F. Xu, J. Duan, "Smoothing of Time-Varying Graph with the Generalized LASSO”, IEEE Access, Volume 9, 2021.

Y. Chi, J. Jiang, F. Zhou, S. Xu, “A Distributed Algorithm for Reconstructing Time-Varying Graph Signals”, Circuits, Systems, and Signal Processing, January 2022.

J. Giraldo, A. Mahmood, B. Garcia-Garcia, D. Thanou, T. Bouwmans, "Reconstruction of Time-varying Graph Signals via Sobolev Smoothness", IEEE Transactions on Signal and Information Processing Over Networks,  March 2022.

J. Castro-Correa, J. Giraldo, A. Mondal, M. Badiey, T. Bouwmans, F. Malliaros, "Time-Varying Signals Recovery Via Graph Neural Networks", IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023, Rhodes Island, Greece, June 2023. 

A. Mondal, M. Das, A. Chatterjee, P. Venkateswaran, “Recovery of Missing Sensor Data by Reconstructing Time-varying Graph Signals”, Preprint, March 2022.

E. Yagamata, S. Ono, "Robust Time-Varying Graph Signal Recovery Over Dynamic Topology", Preprint, 2022.

B. Kartal, E. Özgünay, A. Koc, "Joint Time-Vertex Fractional Fourier Transform", Preprint, March 2022.

N. Rehman, "Time-Varying Graph Mode Decomposition", Preprint, January 2023. 

E. Guneyi, B. Yaldiz, A. Canbolat, E. Vural, "Learning Graph ARMA Processes from Time-Vertex Spectra", Preprint, February 2023.

Y. Zhang, J. Jiang, "Distributed Batch Reconstruction of Time-varying Graph Signals via Sobolev Smoothness on Cartesian Product Graph", Journal of Electronics and Information Technology, February 2023.

J.  Liu, J. Lin, H. Qiu, J. Wang, L. Nong, "Time-varying signal recovery based on low rank and graph-time smoothness", Digital Signal Processing, Volume 133, 2023.

H. Kojima, H. Noguchi, K. Yamada, Y. Tanaka, "Restoration of Time-Varying Graph Signals using Deep Algorithm Unrolling", IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023, Rhodes Island, Greece, 2023.

Z. Xiao, H. Fang, S. Tomasin, G. Mateos, X. Wang, "Joint Sampling and Reconstruction of Time-Varying Signals over Directed Graphs", Transactions on Signal Processing, June 2023.

S. Ji, C. Bu, L. Li, X. Wu, "LocalTGEP: A Lightweight Edge Partitioner for Time-Varying Graph", IEEE Transactions on Emerging Topics in Computing, 2023.

J. Yang, C. Shi, Y. Chu, W. Guo, “Graph Signal Reconstruction based on Spatio-temporal Features Learning”, Digital Signal Processing, February 2024.

M. Nazari, A. Korshoj, N. Rehman, “Multiscale Dynamic Graph Signal Analysis”, SSRN Journal, February 2024.

R. Ye, X. Jiang, H. Feng, J. Wang, R. Qiu, X. Hou, "Time-varying graph learning from smooth and stationary graph signals with hidden nodes", EURASIP Journal on Advances in Signal Processing, March 2024.

J. Castro-Correa, J. Giraldo, M. Badiey, F. Malliaros, "Gegenbauer Graph Neural Networks for Time-varying Signal Reconstruction", Preprint, March 2024.

S. Bagheri, G. Cheung, T. Eadie, A. Ortega, "Joint Signal Interpolation and Time-Varying Graph Estimation via Smoothness and Low-Rank Priors”, IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2024, pages 9646-965,  Seoul, South Korea, 2024.

J. Shi, J. Moura, "Graph Signal Processing: The 2D Companion Model", IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2024, pages 9806-9810, Seoul, South Korea, 2024.

P. Misiakos, V. Mihal, M. Puschel, "Learning Signals and Graphs from Time-Series Graph Data with Few Causes", IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2024, pages 9681-9685, Seoul, South Korea, 2024.

M. Sabbaqi,  E. Isufi, "Inferring Time Varying Signals over Uncertain Graphs," IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2024, pages 9876-9880 , Seoul, South Korea, 2024.

A. Javaheri, A. Amini, F. Marvasti,  D. Palomar, "Joint Signal Recovery and Graph Learning from Incomplete Time-Series", IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2024, pages 13511-13515, Seoul, South Korea, 2024.

T. Alikasifoglu , B. Kartal, A. Koc, "Wiener Filtering in Joint Time-Vertex Fractional Fourier Domains",  IEEE Signal Processing Letters, 2024.

W. Guo, Y. Lou, J. Qin, M. Yan “Time-Varying Graph Signal Recovery Using High-Order Smoothness and Adaptive Low-rankness”, Preprint, May 2024.

D) Adaptive Graph Signal Processing (1 paper)

P. Di Lorenzo, P. Banelli, E. Isufi, S. Barbarossa,  G. Leus, “Adaptive Graph Signal Processing: Algorithms and Optimal Sampling Strategies", IEEE Transactions on Signal Processing, Volume 66, No. 13, pages 3584-3598, 2018.

E) Graph Fourier Transform (14 papers) 

Y. Zhang, B. Li, “The Graph Fractional Fourier Transform in Hilbert Space”, Preprint, April 2024.

D. Pakiyarajah, E. Pavez, A. Ortega, "Irregularity-Aware Bandlimited Approximation for Graph Signal Interpolation", IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2024, pages 9801-9805 , Seoul, South Korea, 2024.

D. Wei, Z. Yan, "Generalized Sampling of Graph Signals with The Prior Information based on Graph Fractional Fourier Transform", Signal Processing, Volume 214, January 2024.

F. Ji, “Lossless Digraph Signal Processing via Polar Decomposition”, Preprint, 2023.

F. Ji, W. P. Tay, A. Ortega, "Graph Signal Processing over a Probability Space of Shift Operators",  IEEE Transactions on Signal Processing, Volume 71, pages 1159-1174, 2023.

H. Zhao, W. Xiang, S. Lv, "A Variable Parameter LMS Algorithm Based on Generalized Maximum Correntropy Criterion for Graph Signal Processing", IEEE Transactions on Signal and Information Processing over Networks, Volume 9, pages 140-151, 2023.

Y. Zhang, B. Li, "The Fractional Fourier Transform on Graphs: Modulation and Convolution", IEEE International Conference on Signal and Image Processing, ICSIP 2023, Wuxi, China, 2023.

D. Wei, Z. Yan, "Sampling of Graph Signals with Successive Aggregations based on Graph Fractional Fourier Transform", Digital Signal Processing, 2023.

Q. Zhang, L. Yang, G. Yang, Z. Yang, "Rating Prediction based on the Graph Fourier Basis and PSD Estimation from the Perspective of Graph Signal Reconstruction", Expert Systems with Applications, 2023.

E. Pavez, B. Girault, A. Ortega, P. Chou, “Two Channel Filter Banks on Arbitrary Graphs with Positive Semi Definite Variation Operators”, Preprint, March 2022.

F. Yan, B. Li, “Multi-dimensional Graph Fractional Fourier Transform and its Application to Data Compression”, Digital Signal Processing, Volume 129, 2022.

F. Ji, W. Tay, “To Further Understand Graph Signals”, Preprint, March 2022.

Y. Wang, B. Li, "The Fractional Fourier Transform on Graphs: Sampling and Recovery", IEEE International Conference on Signal Processing, ICSP 2018, pages 1103-1108, 2018.

T. Kurokawa, T. Oki, H. Nagao, "Multi-dimensional Graph Fourier Transform", Preprint, 2017.

F) Generalized Graph Signal Processing (1 paper)

X. Jian, F.  Ji,  W. Tay, "Generalizing Graph Signal Processing: High Dimensional Spaces, Models and Structures", 2023.

G)  Distributed Graph Signal Processing (3 papers)

D. Tay, “Distributed Graph Regularized Denoising via Constrained Chebyshev Polynomials”, IEEE Signal Processing Letters, 2024.

I. Nobre, P. Frossard, "Optimized Quantization in Distributed Graph Signal Processing," IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2019, Brighton, UK, pages 5376-5380, 2019.

D. Shuman, P. Vandergheynst, D. Kressner, P. Frossard, “Distributed Signal Processing via Chebyshev Polynomial Approximation”, Preprint, 2017.

H) Parallel Graph Signal Processing (1 paper)

D. Dapena, D. Lau, G. R. Arce, "Parallel Graph Signal Processing: Sampling and Reconstruction", IEEE Transactions on Signal and Information Processing over Networks, March 2023.

I) Graph DCT (1 paper)

S.  Pei,  K. Chang, "Diagonalize Integral Graph by DCT", IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2024, pages 13511-13515, Seoul, South Korea, 2024.