March 14, 2024, 4:41 a.m. | Keke Huang, Wencai Cao, Hoang Ta, Xiaokui Xiao, Pietro Li\`o

cs.LG updates on

arXiv:2403.07954v1 Announce Type: new
Abstract: Graph Neural Networks (GNNs), known as spectral graph filters, find a wide range of applications in web networks. To bypass eigendecomposition, polynomial graph filters are proposed to approximate graph filters by leveraging various polynomial bases for filter training. However, no existing studies have explored the diverse polynomial graph filters from a unified perspective for optimization.
In this paper, we first unify polynomial graph filters, as well as the optimal filters of identical degrees into the …

abstract applications arxiv cs.lg eess.sp filter filters gnns graph graph neural networks however networks neural networks novel polynomial studies training type web

Senior Machine Learning Engineer

@ GPTZero | Toronto, Canada

ML/AI Engineer / NLP Expert - Custom LLM Development (x/f/m)

@ HelloBetter | Remote

Senior Research Engineer/Specialist - Motor Mechanical Design

@ GKN Aerospace | Bristol, GB

Research Engineer (Motor Mechanical Design)

@ GKN Aerospace | Bristol, GB

Senior Research Engineer (Electromagnetic Design)

@ GKN Aerospace | Bristol, GB

Associate Research Engineer Clubs | Titleist

@ Acushnet Company | Carlsbad, CA, United States