made to the generic maxent-stress algorithm in order to deal with iMDGP and an extension called wiMDGP. For more technical details we refer the interested reader to our code[^3].

Adapting the Maxent-stress Algorithm for iMDGP
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Recall that for iMDGP we are given a graph $G = (V, E)$ and the distance intervals $d = [l,u] : E \rightarrow \mathbb{R}_{\geq 0}^2$. We then want to find an embedding $x: V \rightarrow \mathbb{R}^3$ that respects the intervals as well as possible. Note that, in line with previous work, we assume the set $S$ of known distances to be equal to $E$ here. We also assume the edges in $E$ to be unweighted.

As Gansner [*et al.*]{}’s maxent-stress algorithm [@gansner2013] cannot cope with intervals, we solve the iMDGP by first running our implementation of the maxent-stress algorithm with an adapted distance $d' : E \rightarrow \mathbb{R}$ that is defined by $d'_{vw} \coloneqq (l_{vw} + u_{vw}) / 2$. One might expect that, in the resulting embedding, the distances should be roughly in the middle of their interval. This would already be a valid solution to the iMDGP. However, our preliminary experiments show that the output of the maxent-stress algorithm still violates distance constraints 