Holistic Graph Neural Networks based on a global-based attention mechanism

A gentle introduction to deep learning for graphs

(2020) Davide Bacciu et al.   NEURAL NETWORKS

M-GWNN: Multi-granularity Graph Wavelet Neural Networks for Semi-supervised Node Classification

(2020) Wenjie Zheng et al.   NEUROCOMPUTING

A deeper graph neural network for recommender systems

(2019) Ruiping Yin et al.   KNOWLEDGE-BASED SYSTEMS

MoleculeNet: a benchmark for molecular machine learning

(2018) Zhenqin Wu et al.   Chemical Science

CayleyNets: Graph Convolutional Neural Networks With Complex Rational Spectral Filters

(2018) Ron Levie et al.   IEEE TRANSACTIONS ON SIGNAL PROCESSING

Geometric Deep Learning: Going beyond Euclidean data

(2017) Michael M. Bronstein et al.   IEEE SIGNAL PROCESSING MAGAZINE

Molecular graph convolutions: moving beyond fingerprints

(2016) Steven Kearnes et al.   JOURNAL OF COMPUTER-AIDED MOLECULAR DESIGN

The emerging field of signal processing on graphs: Extending high-dimensional data analysis to networks and other irregular domains

(2013) D. I. Shuman et al.   IEEE SIGNAL PROCESSING MAGAZINE

Wavelets on graphs via spectral graph theory

(2010) David K. Hammond et al.   APPLIED AND COMPUTATIONAL HARMONIC ANALYSIS

The Graph Neural Network Model

(2008) F. Scarselli et al.   IEEE TRANSACTIONS ON NEURAL NETWORKS