Logical Bayesian networks and their relation to other probabilistic logical models
Abstract Logical Bayesian Networks (LBNs) have recently been introduced as another
language for knowledge based model construction of Bayesian networks, besides existing …
language for knowledge based model construction of Bayesian networks, besides existing …
Learning ground CP-Logic theories by leveraging Bayesian network learning techniques
Causal relations are present in many application domains. Causal Probabilistic Logic (CP-
logic) is a probabilistic modeling language that is especially designed to express such …
logic) is a probabilistic modeling language that is especially designed to express such …
[HTML][HTML] The complexity of Bayesian networks specified by propositional and relational languages
We examine the complexity of inference in Bayesian networks specified by logical
languages. We consider representations that range from fragments of propositional logic to …
languages. We consider representations that range from fragments of propositional logic to …
ALLPAD: Approximate learning of logic programs with annotated disjunctions
F Riguzzi - Machine Learning, 2008 - Springer
Abstract Logic Programs with Annotated Disjunctions (LPADs) provide a simple and elegant
framework for representing probabilistic knowledge in logic programming. In this paper we …
framework for representing probabilistic knowledge in logic programming. In this paper we …
Languages for probabilistic modeling over structured and relational domains
FG Cozman - A Guided Tour of Artificial Intelligence Research …, 2020 - Springer
In this chapter we survey languages that specify probability distributions using graphs,
predicates, quantifiers, fixed-point operators, recursion, and other logical and programming …
predicates, quantifiers, fixed-point operators, recursion, and other logical and programming …
ALLPAD: Approximate learning of logic programs with annotated disjunctions
F Riguzzi - … Logic Programming: 16th International Conference, ILP …, 2007 - Springer
In this paper we present the system ALLPAD for learning Logic Programs with Annotated
Disjunctions (LPADs). ALLPAD modifies the previous system LLPAD in order to tackle real …
Disjunctions (LPADs). ALLPAD modifies the previous system LLPAD in order to tackle real …
Graph sampling with applications to estimating the number of pattern embeddings and the parameters of a statistical relational model
Counting the number of times a pattern occurs in a database is a fundamental data mining
problem. It is a subroutine in a diverse set of tasks ranging from pattern mining to supervised …
problem. It is a subroutine in a diverse set of tasks ranging from pattern mining to supervised …
An integrated development environment for probabilistic relational reasoning
M Finthammer, M Thimm - Logic Journal of IGPL, 2012 - academic.oup.com
This article presents KReator, a versatile integrated development environment for
probabilistic inductive logic programming currently under development. The area of …
probabilistic inductive logic programming currently under development. The area of …
Probabilistic logics in expert systems: Approaches, implementations, and applications
G Kern-Isberner, C Beierle, M Finthammer… - … Conference on Database …, 2011 - Springer
The handling of uncertain information is of crucial importance for the success of expert
systems. This paper gives an overview on logic-based approaches to probabilistic …
systems. This paper gives an overview on logic-based approaches to probabilistic …
[PDF][PDF] Probabilistic logical models for Mendel's experiments: an exercise
H Blockeel - … , 14th International Conference, ILP-2004, Work in …, 2004 - lirias.kuleuven.be
Several probabilistic logical modelling languages are compared on the task of describing or
learning the inheritance mechanism discovered by Mendel. This small exercise reveals …
learning the inheritance mechanism discovered by Mendel. This small exercise reveals …