A Sampling Theory Perspective of Graph-based Semi-supervised Learning

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A Sampling Theory Perspective of Graph-based Semi-supervised Learning

26 May 2017

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Papers citing "A Sampling Theory Perspective of Graph-based Semi-supervised Learning"

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Title
Gegenbauer Graph Neural Networks for Time-varying Signal Reconstruction Jhon A. Castro-Correa Jhony H. Giraldo Mohsen Badiey Fragkiskos D. Malliaros 79 11 0 28 Mar 2024
Graph CNN for Moving Object Detection in Complex Environments from Unseen Videos Jhony H. Giraldo S. Javed Naoufel Werghi T. Bouwmans 40 26 0 13 Jul 2022
Sampling Signals on Graphs: From Theory to Applications Yuichi Tanaka Yonina C. Eldar Antonio Ortega Gene Cheung 58 10 0 09 Mar 2020
GraphBGS: Background Subtraction via Recovery of Graph Signals Jhony H. Giraldo T. Bouwmans 112 25 0 17 Jan 2020
Network Classifiers With Output Smoothing Elsa Rizk Roula Nassif Ali H. Sayed 26 1 0 30 Oct 2019
Laplacian Networks: Bounding Indicator Function Smoothness for Neural Network Robustness Carlos Lassance Vincent Gripon Antonio Ortega AAML 86 16 0 24 May 2018