Computational Capabilities of Graph Neural Networks

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A Comprehensive Survey on Graph Neural Networks

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Graph Deep Learning Model for Mapping Mineral Prospectivity

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Weisfeiler and Leman Go Neural: Higher-Order Graph Neural Networks

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Generalization and Representational Limits of Graph Neural NetworksPreprint

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What Can Neural Networks Reason About?Preprint

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k-hop graph neural networks

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Machine Learning for Scent: Learning Generalizable Perceptual Representations of Small MoleculesPreprint

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Graph neural networks for temperature-dependent activity coefficient prediction of solutes in ionic liquids

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Graph Computing for Financial Crime and Fraud Detection: Trends, Challenges and Outlook

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Financial Crime & Fraud Detection Using Graph Computing: Application Considerations & Outlook

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Combining physics-based and data-driven models: advancing the frontiers of research with scientific machine learning

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iPool—Information-Based Pooling in Hierarchical Graph Neural Networks

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On Inductive–Transductive Learning With Graph Neural Networks

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Explainable AI in drug discovery: self-interpretable graph neural network for molecular property prediction using concept whitening

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Expressivity of Deep Neural Networks

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Visual-Semantic Graph Attention Networks for Human-Object Interaction Detection

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On the complexity of shallow and deep neural network classifiers

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DeepComNet: Performance evaluation of network topologies using graph-based deep learning

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Low-Complexity Recruitment for Collaborative Mobile Crowdsourcing Using Graph Neural Networks

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Recognizing fish behavior in aquaculture with graph convolutional network

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Robust Dual Graph Self-Representation for Unsupervised Hyperspectral Band Selection

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Graph machine learning for design of high‐octane fuels

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Edge-Inferring Graph Neural Network With Dynamic Task-Guided Self-Diagnosis for Few-Shot Hyperspectral Image Classification

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Modular Multi–Source Prediction of Drug Side–Effects With DruGNN

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Target Classification From SAR Imagery Based on the Pixel Grayscale Decline by Graph Convolutional Neural Network

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Classification of Propagation Path and Tweets for Rumor Detection using Graphical Convolutional Networks and Transformer based Encodings

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Graph Neural Network Operators: a Review

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Structured Cooperative Reinforcement Learning With Time-Varying Composite Action Space

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Expressive Power of Invariant and Equivariant Graph Neural NetworksPreprint

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Learning long-term dependencies using layered graph neural networks

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Model complexities of shallow networks representing highly varying functions

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Cooperative Lidar Sensing for Pedestrian Detection: Data Association Based on Message Passing Neural Networks

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Semi-Supervised Self-Correcting Graph Neural Network for Intelligent Fault Diagnosis of Rotating Machinery

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A Heterogeneous Graph Construction Method for Mineral Prospectivity Mapping

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RSI-Net: Two-Stream Deep Neural Network for Remote Sensing Images-Based Semantic Segmentation

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Message Passing Neural Network Versus Message Passing Algorithm for Cooperative Positioning

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Graph Neural Networks are More Powerful than We Think

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Graph Neural Based End-to-end Data Association Framework for Online Multiple-Object TrackingPreprint

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Deep Neural Networks for Structured Data

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Performance Evaluation of Network Topologies using Graph-Based Deep Learning

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Machine Learning Applications for Predicting Fuel Ignition and Flame Properties: Current Status and Future Perspectives

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BioGNN: How Graph Neural Networks Can Solve Biological Problems

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Web Spam Detection by Probability Mapping GraphSOMs and Graph Neural Networks

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Interference recommendation for the pump sizing process in progressive cavity pumps using graph neural networks

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Boosting short term electric load forecasting of high & medium voltage substations with visibility graphs and graph neural networks

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Graph Neural Networks and Boolean SatisfiabilityPreprint

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Protein–Protein Interfaces: A Graph Neural Network Approach

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Addressing data association by message passing over graph neural networks

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Financial Crime & Fraud Detection Using Graph Computing: Application Considerations & OutlookPreprint

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Link-based web spam detection using weight properties

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Drug Side Effect Prediction with Deep Learning Molecular Embedding in a Graph-of-Graphs Domain

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Robust and label efficient bi-filtering graph convolutional networks for node classification

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Graph Neural Network Based Transient Stability Assessment Considering Topology Changes

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Solving graph data issues using a layered architecture approach with applications to web spam detection

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Kernel Robust Soft Learning Vector Quantization

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Graph Learning Network: A Structure Learning AlgorithmPreprint

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Graph-based convolution feature aggregation for retinal vessel segmentation

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The Probabilistic Liveness Decision Method of Unbounded Petri Nets Based on Machine Learning

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A Deep Learning Approach to the Prediction of Drug Side–Effects on Molecular Graphs

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A Machine Learning Approach to Link Prediction for Interlinked Documents

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Systems approaches for synthetic biology: a pathway toward mammalian design

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Predicting scalar coupling constants by graph angle-attention neural network

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On the approximation capability of GNNs in node classification/regression tasks

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Addressing Cold Start in Recommender Systems with Hierarchical Graph Neural Networks

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Changing antibiotic prescribing practices in outpatient primary care settings in China: Study protocol for a health information system-based cluster-randomised crossover controlled trial

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RepGN:Object Detection with Relational Proposal Graph NetworkPreprint

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Weisfeiler–Lehman goes dynamic: An analysis of the expressive power of Graph Neural Networks for attributed and dynamic graphs

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Split Consensus Federated Learning: An Approach for Distributed Training and Inference

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A Simple Spectral Failure Mode for Graph Convolutional Networks

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Towards Heterogeneous Multi-Agent Reinforcement Learning with Graph Neural Networks

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Neural Trees for Learning on GraphsPreprint

Talak, R., Hu, S., Peng, L., & Carlone, L. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2105.07264 · Cited by 9

On the approximation capability of GNNs in node classification/regression tasks

D’Inverno, G. A., Bianchini, M., Sampoli, M. L., & Scarselli, F. (2024) · Soft Computing · doi:10.1007/s00500-024-09676-1 · Cited by 22

The graph neural network model

Scarselli, F., Gori, M., Tsoi, A. C., Hagenbuchner, M., & Monfardini, G. (2009) · IEEE Transactions on Neural Networks · doi:10.1109/tnn.2008.2005605 · Cited by 9,582

An unifying point of view on expressive power of GNNsPreprint

D’Inverno, G. A., Bianchini, M., Sampoli, M. L., & Scarselli, F. (2021) · arXiv (Cornell University) · Cited by 1

Neural function approximation on graphs: shape modelling, graph discrimination & compression

Bouritsas, G. (2023) · doi:10.25560/105560

Theory of graph neural networks: representation and learning

Jegelka, S. (2023) · EMS Press eBooks · doi:10.4171/icm2022/162 · Cited by 36