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GraphMinNet: Learning dependencies in graphs with light complexity minimal architecture.
Graph Neural Networks (GNNs) have demonstrated remarkable success in various applications. Despite their success, traditional GNNs are inherently limited by their local message-passing paradigm and often struggle to capture long-range dependency (LRD) effectively. This paper introduces GraphMinNet,
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