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Found 4 papers, 1 papers with code
Bipartite Graph Variational Auto-Encoder with Fair Latent Representation to Account for Sampling Bias in Ecological Networks
We propose a method to represent bipartite networks using graph embeddings tailored to tackle the challenges of studying ecological networks, such as the ones linking plants and pollinators, where many covariates need to be accounted for, in particular to control for sampling bias.
Impact of the mesoscale structure of a bipartite ecological interaction network on its robustness through a probabilistic modeling
The analysis of a collection of bipartite ecological networks allows us to compare the empirical approach to our probabilistic approach, and illustrates the relevance of the latter when it comes to computing the robustness of a partially observed or incompletely sampled network.
A Stochastic Block Model Approach for the Analysis of Multilevel Networks: an Application to the Sociology of Organizations
A multilevel network is defined as the junction of two interaction networks, one level representing the interactions between individuals and the other the interactions between organizations.
Methodology Applications
Stochastic Block Models for Multiplex networks: an application to networks of researchers
In this paper, we extend the SBM to multiplex networks in order to obtain a clustering based on more than one kind of relationship.
Methodology
