Multiscale Structural Information-Based Laplacian Generative Adversarial Network Representation Learning
In recent years, network representation learning (NRL) has attracted increasing attention due to its efficiency and effectiveness to analyze network structural data. NRL aims to learn low-dimensional representations of nodes while preserving their structural information, and preserving multiscale st...
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| Автори: | , , , |
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| Формат: | Artigo |
| Мова: | Inglês |
| Опубліковано: |
IEEE
2025-01-01
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| Серія: | IEEE Access |
| Предмети: | |
| Онлайн доступ: | https://ieeexplore.ieee.org/document/10965639/ |
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