This paper applies probabilistic model checking techniques for discrete Markov chains to
inference in Bayesian networks. We present a simple translation from Bayesian networks …

Abstract Recently, Probabilistic Circuits such as Sum-Product Networks have received
growing attention, as they can represent complex features but still provide tractable …

Smart portable applications increasingly rely on edge computing due to privacy and latency
concerns. But guaranteeing always-on functionality comes with two major challenges …

Smart portable applications increasingly rely on edge computing due to privacyand latency
concerns. But guaranteeing always-on functionality comes with twomajor challenges …

Probabilistic (logic) programs are routinely compiled into arithmetic circuits. During such a
compilation step, the logic representation of a probabilistic program is transformed into an …

Edge reasoning attempts to mitigate latency and privacy shortcomings of cloud computing
paradigms. However, it introduces additional challenges linked to the devices' resource …

This chapter introduces a hardware-aware optimization technique for Probabilistic Circuits, a
state-of-the-art deep probabilistic model that enables efficient inference and that can …

Weighted model integration (WMI) is a very appealing framework for probabilistic inference:
it allows to express the complex dependencies of real-world hybrid scenarios where …