Version 1.2 of the stochastic weight estimators have been released, including in the ProM nightly build.

These plugins allow labelled stochastic Petri nets to be discovered from an input event log and (vanilla) Petri net. There’s also a convenience plugin that first uses the Inductive Miner, then the Alignment estimator, to build a weighted Petri net directly from a log. More detail in this post and preprint; some other researchers have also proposed estimators since then.

The big two changes are a much prettier visualisation, and a fix to an infuriating bug that stopped the plugin working in released versions of ProM, but not in any development environment where it could be tested.

The pretty new visualisation is from Adam Banham. You can see it at work in his paper Discovering the Influence of Exogenous Data on Decisions in Processes preprint. Thanks Adam! Visualiser for ProM GSPNs

References

Banham, A., Bertrand, Y., Andrews, R., Wynn, M. T., & Leemans, S. J. (2025, June). Discovering the Influence of Exogenous Data on Decisions in Processes. In International Conference on Applications and Theory of Petri Nets and Concurrency (pp. 41-62).

Burke, A, Leemans, S.J.J. and Wynn, M.T. (2020). Stochastic Process Discovery By Weight Estimation. International Workshop on Process Querying, Manipulation, and Intelligence 2020.