arXiv:2301.11290
공식 코드 · Papers with Code
Graph Encoder Ensemble for Simultaneous Vertex Embedding and Community Detection
원문 초록
In this paper, we introduce a novel and computationally efficient method for vertex embedding, community detection, and community size determination. Our approach leverages a normalized one-hot graph encoder and a rank-based cluster size measure. Through extensive simulations, we demonstrate the excellent numerical performance of our proposed graph encoder ensemble algorithm.
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Breaking the Batch Barrier (B3) of Contrastive Learning via Smart Batch Mining
Advancing Community Detection with Graph Convolutional Neural Networks: Bridging Topological and Attributive Cohesion
Community and hyperedge inference in multiple hypergraphs
Adaptive Long-term Embedding with Denoising and Augmentation for Recommendation
Robust Markov stability for community detection at a scale learned based on the structure
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