Before revision:  While many probabilistic generative models for graph clustering have been proposed , there are relatively few such models for hypergraphs. We propose a Poisson degree-corrected hypergraph stochastic blockmodel (DCHSBM), an expressive generative model of clustered hypergraphs with heterogeneous node degrees and edge sizes.
After revision:  While many probabilistic generative models for graph clustering have been proposed , there are few models and algorithms for hypergraph clustering. Here, we propose a Poisson degree-corrected hypergraph stochastic blockmodel (DCHSBM), an expressive generative model of clustered hypergraphs with heterogeneous node degrees and edge sizes.