7 citations · 29 across the 33 of their papers we have counts for
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cs.LG2022★ 2 cited
Generalized energy and gradient flow via graph framelets
Andi Han, Dai Shi, Zhiqi Shao +1
In this work, we provide a theoretical understanding of the framelet-based graph neural networks through the perspective of energy gradient flow. By viewing the framelet-based mode…
cs.LG2022
Generalized Laplacian Regularized Framelet Graph Neural Networks
Zhiqi Shao, Andi Han, Dai Shi +2
This paper introduces a novel Framelet Graph approach based on p-Laplacian GNN. The proposed two models, named p-Laplacian undecimated framelet graph convolution (pL-UFG) and gener…
cs.LG2022★ 4 cited
Quasi-Framelets: Robust Graph Neural Networks via Adaptive Framelet Convolution
Mengxi Yang, Dai Shi, Xuebin Zheng +2
This paper aims to provide a novel design of a multiscale framelet convolution for spectral graph neural networks (GNNs). While current spectral methods excel in various graph lear…