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- Daan Fierens, Guy Van den Broeck, +5 authors Luc De Raedt
- TPLP
- 2015
Probabilistic logic programs are logic programs in which some of the facts are annotated with probabilities. This paper investigates how classical inference and learning tasks known from the… (More)
We review Logical Bayesian Networks, a language for probabilistic logical modelling, and discuss its relation to Probabilistic Relational Models and Bayesian Logic Programs. 1 Probabilistic Logical… (More)
Probabilistic logic programs are logic programs in which some of the facts are annotated with probabilities. Several classical probabilistic inference tasks (such as MAP and computing marginals) have… (More)
- Nima Taghipour, Daan Fierens, Jesse Davis, Hendrik Blockeel
- J. Artif. Intell. Res.
- 2013
Lifted probabilistic inference algorithms exploit regularities in the structure of graphical models to perform inference more efficiently. More specifically, they identify groups of interchangeable… (More)
- Luc De Raedt, Bart Demoen, +10 authors Joost Vennekens
- 2008
This paper reports on our work towards the development of a probabilistic logic programming environment intended as a target language in which other probabilistic languages can be compiled, thereby… (More)
- Jan Ramon, Daan Fierens, +4 authors Greta Van den Berghe
- Advanced Engineering Informatics
- 2007
In this paper we describe the application of data mining methods for predicting the evolution of patients in an intensive care unit. We discuss the importance of such methods for health care and… (More)
- Nima Taghipour, Daan Fierens, Guy Van den Broeck, Jesse Davis, Hendrik Blockeel
- AISTATS
- 2013
Lifting aims at improving the efficiency of probabilistic inference by exploiting symmetries in the model. Various methods for lifted probabilistic inference have been proposed, but our understanding… (More)
- Hossein Rahmani, Beau Piccart, Daan Fierens, Hendrik Blockeel
- CAMRa '10
- 2010
We describe three different approaches to the Context Aware Movie Recommendation (CAMRa) challenge. Each approach is based on different machine learning techniques: two are nearest neighbor… (More)
For many tasks in fields like computer vision, computational biology and information extraction, popular probabilistic inference methods have been devised mainly for propositional models that contain… (More)
- Daan Fierens
- ILP
- 2009
A significant part of current research on ILP deals with proba bilistic logical models. Over the last decade many logics or language s for representing such models have been introduced. There is… (More)