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Deep Learning With Graph-Structured Representations
Novel approaches based on the theme of structuring the representations and computations of neural network-based models in the form of a graph.
graph-neural-networks graph-convolutional-networks graph-auto-encoders relational-graph-convolutional-networks
A pytorch adversarial library for attack and defense methods on images and graphs.
adversarial-learning adversarial-attacks adversarial-defense pytorch
Do we Need Deep Graph Neural Networks?
Does depth in graph neural network architectures bring any advantage?
graph-neural-networks depth graphs tutorial
Temporal Graph Networks
In this post, we describe Temporal Graph Network, a generic framework for deep learning on dynamic graphs.
graph-neural-networks temporal-graph-networks graphs article
GNNExplainer: Generating Explanations for Graph Neural Networks
General tool for explaining predictions made by graph neural networks (GNNs).
graph-neural-networks interpretability explainability graphs
Machine Learning on Graphs: A Model and Comprehensive Taxonomy
We propose a simple framework (GraphEDM) and a comprehensive Taxonomy to review and unify several graph representation learning methods.
graph-neural-networks graph-convolutional-networks autoencoders graph-regularization
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AI Research @apple. Author @oreillymedia. ML Lead @Ciitizen. Alum @hopkinsmedicine and @gatech
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