AIMC Topic: Graph Neural Networks

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User preference interaction fusion and swap attention graph neural network for recommender system.

Neural networks : the official journal of the International Neural Network Society Jan 4, 2025
Recommender systems are widely used in various applications. Knowledge graphs are increasingly used to improve recommendation performance by extracting valuable information from user-item interactions. However, current methods do not effectively use ...
Algorithms Attention Graph Neural Networks Humans Neural Networks, Computer
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On the probability of necessity and sufficiency of explaining Graph Neural Networks: A lower bound optimization approach.

Neural networks : the official journal of the International Neural Network Society Dec 24, 2024
The explainability of Graph Neural Networks (GNNs) is critical to various GNN applications, yet it remains a significant challenge. A convincing explanation should be both necessary and sufficient simultaneously. However, existing GNN explaining appr...
Humans Neural Networks, Computer Algorithms Graph Neural Networks Probability
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Heterophilous distribution propagation for Graph Neural Networks.

Neural networks : the official journal of the International Neural Network Society Dec 24, 2024
Graph Neural Networks (GNNs) have achieved remarkable success in various graph mining tasks by aggregating information from neighborhoods for representation learning. The success relies on the homophily assumption that nearby nodes exhibit similar be...
Humans Graph Neural Networks Neural Networks, Computer Algorithms
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Drug toxicity prediction model based on enhanced graph neural network.

Computers in biology and medicine Dec 24, 2024
Prediction of drug toxicity remains a significant challenge and an essential process in drug discovery. Traditional machine learning algorithms struggle to capture the full scope of molecular structure features, limiting their effectiveness in toxici...
Neural Networks, Computer Algorithms Drug-Related Side Effects and Adverse Reactions Databases, Factual Humans Graph Neural Networks
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Implementing the discontinuous-Galerkin finite element method using graph neural networks with application to diffusion equations.

Neural networks : the official journal of the International Neural Network Society Dec 19, 2024
Machine learning (ML) has benefited from both software and hardware advancements, leading to increasing interest in capitalising on ML throughout academia and industry. There have been efforts in the scientific computing community to leverage this de...
Graph Neural Networks Neural Networks, Computer Algorithms Machine Learning Finite Element Analysis
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Brain networks and intelligence: A graph neural network based approach to resting state fMRI data.

Medical image analysis Dec 16, 2024
Resting-state functional magnetic resonance imaging (rsfMRI) is a powerful tool for investigating the relationship between brain function and cognitive processes as it allows for the functional organization of the brain to be captured without relying...
Graph Neural Networks Intelligence Nerve Net Male Adolescent Magnetic Resonance Imaging Brain Mapping Humans Brain Neural Networks, Computer Female
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circ2DGNN: circRNA-Disease Association Prediction via Transformer-Based Graph Neural Network.

IEEE/ACM transactions on computational biology and bioinformatics Dec 10, 2024
Investigating the associations between circRNA and diseases is vital for comprehending the underlying mechanisms of diseases and formulating effective therapies. Computational prediction methods often rely solely on known circRNA-disease data, indire...
RNA, Circular Graph Neural Networks Algorithms Computational Biology Humans Neural Networks, Computer
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An End-to-End Knowledge Graph Fused Graph Neural Network for Accurate Protein-Protein Interactions Prediction.

IEEE/ACM transactions on computational biology and bioinformatics Dec 10, 2024
Protein-protein interactions (PPIs) are essential to understanding cellular mechanisms, signaling networks, disease processes, and drug development, as they represent the physical contacts and functional associations between proteins. Recent advances...
Computational Biology Humans Proteins Neural Networks, Computer Graph Neural Networks Databases, Protein Algorithms Protein Interaction Mapping Protein Interaction Maps
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Super-fast and accurate nonlinear foot deformation Prediction using graph neural networks.

Journal of the mechanical behavior of biomedical materials Dec 9, 2024
Recently, there has been a significant increase in the number of foot diseases, highlighting the importance of non-surgical treatments. Customized insoles, tailored to an individual's foot morphology, have emerged as a promising solution. However, th...
Humans Time Factors Nonlinear Dynamics Foot Neural Networks, Computer Biomechanical Phenomena Graph Neural Networks Mechanical Phenomena Finite Element Analysis
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MDMNI-DGD: A novel graph neural network approach for druggable gene discovery based on the integration of multi-omics data and the multi-view network.

Computers in biology and medicine Dec 6, 2024
Accurately predicting druggable genes is of paramount importance for enhancing the efficacy of targeted therapies, reducing drug-related toxicities and improving patients' survival rates. Nevertheless, accurately predicting candidate cancer-druggable...
Neural Networks, Computer Neoplasms Databases, Genetic Gene Regulatory Networks Graph Neural Networks Genomics Computational Biology Protein Interaction Maps Multiomics Humans
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