Fuzzy Message Passing in Graph Neural Networks: A First Approach to Uncertainty in Node Embeddings

Duong, Minh Tuan

Fuzzy Message Passing in Graph Neural Networks: A First Approach to Uncertainty in Node Embeddings

Duong, Minh Tuan (2025) Fuzzy Message Passing in Graph Neural Networks: A First Approach to Uncertainty in Node Embeddings. EAI Endorsed Transactions on Contex-aware Systems and Applications.

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Abstract

Graph Neural Networks (GNNs) have emerged as a powerful tool for learning representations in graph structured data. However, traditional message-passing mechanisms often struggle with uncertainty and noise in node features and graph topology. In this paper, we propose Fuzzy Message Passing (FMP), a

Item Type:	Article
Date Deposited:	04 Mar 2026 20:14
Last Modified:	16 Apr 2026 16:08
URI:	http://eprints.eai.eu/id/eprint/59856

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