The paper noDice: Inference for Discrete Probabilistic Programs with Nondeterminism and Conditioning by Tobias Gürtler and Benjamin Kaminski has been accepted for publication at the International Conference on Object-Oriented Programming Systems, Languages, and Applications (OOPSLA 2026). It presents a novel inference algorithm for discrete, loop-free probabilisitic programs that additionally feature (non-probabilistic) nondeterminism.

Our paper Generative Datalog with Continuous Distributions (joint work with Martin Grohe, Joost-Pieter Katoen, and Peter Lindner) was featured as one of eight selected articles published in 2022 in the Journal of the ACM. It describes a new way to give semantics to Datalog, a declarative probabilistic programming language used in the context of probabilistic…

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