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Neural Networks Are Graphs! Graph Neural Networks for Equivariant Processing of Neural Networks
2023Neural networks that can process the parameters of other neural networks find applications in diverse domains, including processing implicit neural representations, domain adaptation of pretrained networks, generating neural network weights, and predicting generalization errors.
Zhang, D.W. +5 more
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Graph Neural Networks : Graph Representation Learning using Neural Networks
This book, "Graph Neural Networks: Graph Representation Learning with a Neural Network Approach," offers a comprehensive and up-to-date guide to the dynamic field of Graph Neural Networks (GNNs). It serves as an essential Persian-language resource for students, researchers, and AI practitioners.Boreiri, Zahra +2 more
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Integrative oncology: Addressing the global challenges of cancer prevention and treatment
Ca-A Cancer Journal for Clinicians, 2022Jun J Mao,, Msce +2 more
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Graph Neural Networks: Graph Transformation
2022Xiaojie Guo, Shiyu Wang, Liang Zhao
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Multidisciplinary standards of care and recent progress in pancreatic ductal adenocarcinoma
Ca-A Cancer Journal for Clinicians, 2020Aaron J Grossberg +2 more
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