Graph signal processing for machine learning: A review and new
perspectives

Graph signal processing for machine learning: A review and new perspectives

31 July 2020

Papers citing "Graph signal processing for machine learning: A review and new perspectives"

13 / 13 papers shown

Title
Learning Sheaf Laplacian Optimizing Restriction Maps Leonardo Di Nino Sergio Barbarossa P. Di Lorenzo 47 0 0 31 Jan 2025
A Review of Graph-Powered Data Quality Applications for IoT Monitoring Sensor Networks Pau Ferrer-Cid Jose M. Barcelo-Ordinas J. García-Vidal 37 2 0 28 Oct 2024
Learning signals defined on graphs with optimal transport and Gaussian process regression Raphael Carpintero Perez Sébastien da Veiga Josselin Garnier B. Staber 28 1 0 21 Oct 2024
Online Graph Filtering Over Expanding Graphs Bishwadeep Das Elvin Isufi 23 0 0 11 Sep 2024
Bayesian Optimization of Functions over Node Subsets in Graphs Huidong Liang Xingchen Wan Xiaowen Dong 40 1 0 24 May 2024
Through the Dual-Prism: A Spectral Perspective on Graph Data Augmentation for Graph Classification Yutong Xia Runpeng Yu Yuxuan Liang Xavier Bresson Xinchao Wang Roger Zimmermann 35 4 0 18 Jan 2024
Learning the hub graphical Lasso model with the structured sparsity via an efficient algorithm Chengjing Wang Peipei Tang Wen-Bin He Meixia Lin 22 0 0 17 Aug 2023
Graph Federated Learning for CIoT Devices in Smart Home Applications Arash Rasti-Meymandi S. M. Sheikholeslami J. Abouei Konstantinos N. Plataniotis FedML 15 18 0 29 Dec 2022
Challenges in anomaly and change point detection Madalina Olteanu Fabrice Rossi Florian Yger 14 0 0 27 Dec 2022
Laplacian Constrained Precision Matrix Estimation: Existence and High Dimensional Consistency E. Pavez 9 4 0 31 Oct 2021
How Powerful is Graph Convolution for Recommendation? Yifei Shen Yongji Wu Yao Zhang Caihua Shan Jun Zhang Khaled B. Letaief Dongsheng Li GNN 13 99 0 17 Aug 2021
Geometric deep learning on graphs and manifolds using mixture model CNNs Federico Monti Davide Boscaini Jonathan Masci Emanuele Rodolà Jan Svoboda M. Bronstein GNN 234 1,801 0 25 Nov 2016
Geometric deep learning: going beyond Euclidean data M. Bronstein Joan Bruna Yann LeCun Arthur Szlam P. Vandergheynst GNN 231 3,202 0 24 Nov 2016