WebNov 1, 2024 · Abstract: Graph Convolutional Networks (GCNs) have fueled a surge of interest due to their superior performance on graph learning tasks, but are also shown … WebMay 24, 2024 · As an alternative, we propose an operator based on graph powering, and prove that it enjoys a desirable property of "spectral separation." Based on the operator, we propose a robust learning paradigm, where the network is trained on a family of "'smoothed" graphs that span a spatial and spectral range for generalizability.
Stealing Links from Graph Neural Networks USENIX
WebGraph Attention Networks over Edge Content-Based Channels. ... Graph structural attack by perturbing spectral distance. L Lin, E Blaser, H Wang. ... Spectral Augmentation for … WebGraph Structural Attack by Perturbing Spectral Distance Lu Lin [email protected] University of Virginia Charlottesville, VA 22904, USA ... Graph Structural Attack by … child desk chair with storage
An Experimental Study of the Transferability of Spectral Graph
WebJun 1, 2024 · Graph Structural Attack by Spectral Distanc Preprint Nov 2024 Lu Lin Ethan Blaser Hongning Wang View Show abstract ... A steganography based universal adversarial perturbation method is... WebNov 1, 2024 · In this paper, an effective graph structural attack is investigated to disrupt graph spectral filters in the Fourier domain. We define the spectral distance based on … WebNov 1, 2024 · In this paper, an effective graph structural attack is investigated to disrupt graph spectral filters in the Fourier domain. We define the spectral distance based on the eigenvalues... child developed a tic