图信号处理并且非图神经网络的论文：

Donget.al“GraphSignal Processingfor MachineLearning A Review and New Perspectives," ICASSP Tutorial, June 2021.

Lorenzoet.al“Adaptiveleast mean squaresestimation ofgraph signals"IEEE Trans. Signal Inf. Process. Netw., 2016

G-LMS and variants

·Lorenzoet.al"Adaptive least mean squares estimation of graph signals"lEEE Trans. Signal Information Process. Networks, 2016.·Underlying Gaussianity assumption
· Not robust against (non-Gaussian) noise· Normalised version:G-NLMS
·SpeltaandMartins“Normalized LMS algorithm and data-selective strategies for adaptive graph signal estimation,“ Signal Processing,2020.·Lp-norm version: G-LMP and G-NLMP
Nguyenetal.Adaptive estimation and sparse sampling for graph signals in alpha-stable noise, Digital Signal Processing,2020.
Yanetal.Graph Normalized-LMP Algorithm for Signal Estimation Under Impulsive Noise.J Signal Processing Systems,2022.

Yi Yan,ErcanE.Kuruoglu, and MustafaA.Altinkaya,“Adaptive SignAlgorithm for Graph Signal Processing" Signal Processing, 2022

S.Barbarossa,Topological Signal Processing and Learning, DEGAS,2022

S.Barbarossa,S.Sardelitti,Topological Signal ProcessingOver Simplicial Complexes, IEEE Trans. Signal Proc.2020

Y.YanTXie.E.E.Kuruoqlu,JointEstimation ofMulti-order Graph Topological Signals, submitted to ICASSP 2023

M.J.M.Spelta.W.A.Martins.NormalizedLMSalaorithm and data-selective strateaies for adaptive araph sianal estimation. Siana Processing. Volume 167.2020

*G.Panagopoulos,G.Nikolentzos,M.Vazirgiannis,Transfer Graph Neural Networks for Pandemic Forecasting, AAAI 2021