Mar 3, 2020 · In this work, we propose a new strategy for pooling and sampling on GNNs using graphons which preserves the spectral properties of the graph. To ...
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Mar 3, 2020 · In this work, we propose a new strategy for pooling and sampling on GNNs using graphons which preserves the spectral properties of the graph. To ...
These results apply in commutative scenarios such as graph filters and graph neural networks [5], Euclidean filters and traditional convolutional neural ...
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Mar 3, 2020 · This work proposes a new strategy for pooling and sampling on GNNs using graphons which preserves the spectral properties of the graph and ...
Pooling in graph neural networks : r/neuralnetworks - Reddit
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Nov 30, 2023 · You can think of pooling as an aggregation step that averages (this is called mean pooling) the embeddings of all the neighbors of a particular node to ...
Missing: Graphon | Show results with:Graphon
Abstract—In this paper we propose a pooling approach for convolutional information processing on graphs relying on the theory of graphons and limits of ...
Duration: 14:23
Posted: Dec 10, 2020
Posted: Dec 10, 2020
Mar 11, 2020 · In this work, we propose a new strategy for pooling and sampling on GNNs using graphons which preserves the spectral properties of the graph. To ...
Sep 22, 2023 · In this article we propose a pooling approach for convolutional information processing on graphs relying on the theory of graphons and ...
Graphons are general and powerful models for generating graphs of varying size. In this pa- per, we propose to directly model graphons us- ing neural ...