Learning of weighted multi-layer networks via dynamic social spaces, with application to financial interbank transactions
We propose a general network model suited for longitudinal data of multi-layer networks with directed and weighted edges. Our formulation built upon the latent social space representation of networks. It consists of a hierarchical formulation: deep levels of the model represent latent coordinates of...
| Main Authors: | , |
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| Format: | Conference item |
| Language: | English |
| Published: |
Springer
2019
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