Predicting variable-length paths in networked systems using multi-order generative models
Abstract Apart from nodes and links, for many networked systems, we have access to data on paths, i.e., collections of temporally ordered variable-length node sequences that are constrained by the system’s topology. Understanding the patterns in such data is key to advancing our understanding of the...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2023-09-01
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| Series: | Applied Network Science |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/s41109-023-00596-x |