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network-perturbation

topic1 events
papersSEP 10 04:00 UTC

Study examines robustness of shallow graph embeddings for community detection

A paper on arXiv investigates how well shallow graph embedding methods for community detection hold up when networks undergo perturbations, focusing on node deletions. It evaluates whether low-dimensional node representations preserve community structure as the underlying graph changes. The work offers insight into when these embedding techniques remain reliable in practice.

graph-learning/community-detection/robustness