111 citations · 179 across the 22 of their papers we have counts for
23 papers
smProbLog: Stable Model Semantics in ProbLog for Probabilistic Argumentation
Pietro Totis, Angelika Kimmig, Luc De Raedt
Argumentation problems are concerned with determining the acceptability of a set of arguments from their relational structure. When the available information is uncertain, probabil…
Neural Probabilistic Logic Programming in Discrete-Continuous Domains
Lennert De Smet, Pedro Zuidberg Dos Martires, Robin Manhaeve +3
Neural-symbolic AI (NeSy) allows neural networks to exploit symbolic background knowledge in the form of logic. It has been shown to aid learning in the limited data regime and to…
Declarative Probabilistic Logic Programming in Discrete-Continuous Domains
Pedro Zuidberg Dos Martires, Luc De Raedt, Angelika Kimmig
Over the past three decades, the logic programming paradigm has been successfully expanded to support probabilistic modeling, inference and learning. The resulting paradigm of prob…
Efficient Knowledge Compilation Beyond Weighted Model Counting
Rafael Kiesel, Pietro Totis, Angelika Kimmig
Quantitative extensions of logic programming often require the solution of so called second level inference tasks, i.e., problems that involve a third operation, such as maximizati…
Using DeepProbLog to perform Complex Event Processing on an Audio Stream
Marc Roig Vilamala, Tianwei Xing, Harrison Taylor +6
In this paper, we present an approach to Complex Event Processing (CEP) that is based on DeepProbLog. This approach has the following objectives: (i) allowing the use of subsymboli…
SMProbLog: Stable Model Semantics in ProbLog and its Applications in Argumentation
Pietro Totis, Angelika Kimmig, Luc De Raedt
We introduce SMProbLog, a generalization of the probabilistic logic programming language ProbLog. A ProbLog program defines a distribution over logic programs by specifying for eac…