Jan 18, 2024 · We propose a novel Graph Power Filter Neural Network (GPFN) that enhances node classification by employing a power series graph filter to augment the receptive ...

These filters are mainly aimed at filtering information between two layers, without introducing more layer parameters. Spectral GNNs are grounded in the concept ...

Title: Infinite-Horizon Graph Filters: Leveraging Power Series to Enhance Sparse Information Aggregation. Authors: Ruizhe Zhang 0013, Xinke Jiang, Yuchen Fang, ...

Apr 21, 2024 · This paper introduces a novel approach to graph neural networks (GNNs) called "infinite-horizon graph filters" that leverages power series to ...

Jan 19, 2024 · [2401.09943] Infinite-Horizon Graph Filters: Leveraging Power Series to Enhance Sparse Information Aggregation. arxiv.org. Open. Upvote 1

Graph Neural Networks (GNNs) have shown considerable effectiveness in a variety of graph learning tasks, particularly those based on the message-passing ...

Infinite-Horizon Graph Filters: Leveraging Power Series to Enhance Sparse Information Aggregation ... Graph Neural Networks (GNNs) have shown considerable ...

Infinite-Horizon Graph Filters: Leveraging Power Series to Enhance Sparse Information Aggregation · 1 code implementation • 18 Jan 2024 • Ruizhe Zhang, Xinke ...

Aug 20, 2024 · Infinite-Horizon Graph Filters: Leveraging Power Series to Enhance Sparse Information Aggregation. CoRR abs/2401.09943 (2024). [i3]. view.

2024. Infinite-horizon graph filters: Leveraging power series to enhance sparse information aggregation. R Zhang*, X Jiang*, Y Fang*, J Luo, Y Xu, Y Zhu, X ...