Fast and scalable likelihood maximization for Exponential Random Graph Models with local constraints
Abstract Exponential Random Graph Models (ERGMs) have gained increasing popularity over the years. Rooted into statistical physics, the ERGMs framework has been successfully employed for reconstructing networks, detecting statistically significant patterns in graphs, counting networked configuration...
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| Main Authors: | , , , , , , , |
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| Format: | article |
| Language: | EN |
| Published: |
Nature Portfolio
2021
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| Subjects: | |
| Online Access: | https://doaj.org/article/00f9f8db37124723b7faa9a1b6954d4c |
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