SpaPool: Soft Partition Assignment Pooling for__Graph Neural Networks

• URL: http://arxiv.org/abs/2509.11675v2
• Date: Tue, 14 Oct 2025 11:23:36 GMT
• Title: SpaPool: Soft Partition Assignment Pooling for__Graph Neural Networks
• Authors: Rodrigue Govan, Romane Scherrer, Philippe Fournier-Viger, Nazha Selmaoui-Folcher,
• Abstract summary: This paper introduces SpaPool, a novel pooling method for a graph neural network.<n>It combines the strengths of both dense and sparse techniques for a graph neural network.<n>It aims to maintain the structural integrity of the graph while reducing its size efficiently.
• Score: 3.634532073343371
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: This paper introduces SpaPool, a novel pooling method that combines the strengths of both dense and sparse techniques for a graph neural network. SpaPool groups vertices into an adaptive number of clusters, leveraging the benefits of both dense and sparse approaches. It aims to maintain the structural integrity of the graph while reducing its size efficiently. Experimental results on several datasets demonstrate that SpaPool achieves competitive performance compared to existing pooling techniques and excels particularly on small-scale graphs. This makes SpaPool a promising method for applications requiring efficient and effective graph processing.

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