3 citations · 4 across the 4 of their papers we have counts for
5 papers · 1 filter
Handling Epistemic and Aleatory Uncertainties in Probabilistic Circuits
Federico Cerutti, Lance M. Kaplan, Angelika Kimmig +1
When collaborating with an AI system, we need to assess when to trust its recommendations. If we mistakenly trust it in regions where it is likely to err, catastrophic failures may…
Process Discovery for Structured Program Synthesis
Dell Zhang, Alexander Kuhnle, Julian Richardson +1
A core task in process mining is process discovery which aims to learn an accurate process model from event log data. In this paper, we propose to use (block-) structured programs…
SHACL Constraints with Inference Rules
Paolo Pareti, George Konstantinidis, Timothy J. Norman +1
The Shapes Constraint Language (SHACL) has been recently introduced as a W3C recommendation to define constraints that can be validated against RDF graphs. Interactions of SHACL wi…
Uncertainty Aware AI ML: Why and How
Lance Kaplan, Federico Cerutti, Murat Sensoy +2
This paper argues the need for research to realize uncertainty-aware artificial intelligence and machine learning (AI\&ML) systems for decision support by describing a number of mo…
Probabilistic Logic Programming with Beta-Distributed Random Variables
Federico Cerutti, Lance Kaplan, Angelika Kimmig +1
We enable aProbLog---a probabilistic logical programming approach---to reason in presence of uncertain probabilities represented as Beta-distributed random variables. We achieve th…