As our model is based on populating a latent "event space" into boxes (products of intervals), it is especially reminiscent of the Mondrian process (Roy and Teh, 2009).
the Mondrian process partitions the space as a high dimensional tree (a non-parametric kd-tree), while our model allows the arbitrary box placement required for DAG structure, and is much more tractable in high dimensions compared to the Mondrian's Bayesian non-parametric inference.