heterophily
ae07d152c51ea2ddae65aa7192eb5ff7-Supplemental-Conference.pdf
Recent work has shown that a much simpler model, simple graph convolution (SGC) (Wu et al., 2019),iscompetitivewithGCNs incommon graph machine learning benchmarks.
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From Trainable Negative Depth to Edge Heterophily in Graphs Y uchen Y an
Upon increasing the depth, the over-smoothing issue arises: a GCN's
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ae07d152c51ea2ddae65aa7192eb5ff7-Paper-Conference.pdf
Recent work has shown that a much simpler model, simple graph convolution (SGC) (Wu et al., 2019),iscompetitivewithGCNs incommon graph machine learning benchmarks.
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Scalable Heterophilous Graph Neural Network with Decoupled Embeddings
However, this assumption does not always hold in practice.
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Technology: Information Technology > Artificial Intelligence > Machine Learning > Neural Networks (1.00)
Revisiting Heterophily For Graph Neural Networks
Graph Neural Networks (GNNs) extend basic Neural Networks (NNs) by using graph structures based on the relational inductive bias (homophily assumption).
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