Logical Bayesian Networks and Their Relation to Other Probabilistic Logical Models. - Daan Fierens; Hendrik Blockeel; Maurice Bruynooghe; Jan Ramon (BNAIC, 2005)

A Comparison of Approaches for Learning Probability Trees. - Daan Fierens; Jan Ramon; Hendrik Blockeel; Maurice Bruynooghe (ECML, 2005)

Learning Directed Probabilistic Logical Models Using Ordering-Search. - Daan Fierens; Jan Ramon; Maurice Bruynooghe; Hendrik Blockeel (ILP, 2007)

Mining data from intensive care patients. - Jan Ramon; Daan Fierens; Fabian Güiza Grandas; Geert Meyfroidt; Hendrik Blockeel; Maurice Bruynooghe; Greta Van den Berghe (Adv. Eng. Informatics, 2007)

Learning directed probabilistic logical models from relational data. - Daan Fierens (AI Commun., 2008)

Learning directed probabilistic logical models: ordering-search versus structure-search. - Daan Fierens; Jan Ramon; Maurice Bruynooghe; Hendrik Blockeel (Ann. Math. Artif. Intell., 2008)

Generalized ordering-search for learning directed probabilistic logical models. - Jan Ramon; Tom Croonenborghs; Daan Fierens; Hendrik Blockeel; Maurice Bruynooghe (Mach. Learn., 2008)

On the Relationship between Logical Bayesian Networks and Probabilistic Logic Programming Based on the Distribution Semantics. - Daan Fierens (ILP, 2009)

An Exercise with Statistical Relational Learning Systems. - Maurice Bruynooghe; Daan Fierens; Bernd Gutmann; Angelika Kimmig; Niels Landwehr; Wannes Meert; Ingo Thon; Luc De Raedt (MLG/SRL@ILP, 2009)

Context-Specific Independence in Directed Relational Probabilistic Models and its Influence on the Efficiency of Gibbs Sampling. - Daan Fierens (ECAI, 2010)

Improving the Efficiency of Gibbs Sampling for Probabilistic Logical Models by Means of Program Specialization. - Daan Fierens (ICLP (Technical Communications), 2010)

On the Use of Combining Rules in Relational Probability Trees. - Daan Fierens (SDM, 2010)

A comparison of pruning criteria for probability trees. - Daan Fierens; Jan Ramon; Hendrik Blockeel; Maurice Bruynooghe (Mach. Learn., 2010)

Inference in Probabilistic Logic Programs using Weighted CNF's. - Daan Fierens; Guy Van den Broeck; Ingo Thon; Bernd Gutmann; Luc De Raedt (UAI, 2011)

Improving the Efficiency of Approximate Inference for Probabilistic Logical Models by means of Program Specialization - Daan Fierens (CoRR, 2011)

Pairwise Markov Logic. - Daan Fierens; Kristian Kersting; Jesse Davis; Jian Chen; Martin Mladenov (ILP, 2012)

From Lifted Inference to Lifted Models. - Daan Fierens; Kristian Kersting (StarAI@UAI, 2012)

Lifted Variable Elimination: A Novel Operator and Completeness Results - Nima Taghipour; Daan Fierens; Guy Van den Broeck; Jesse Davis; Hendrik Blockeel (CoRR, 2012)

Lifted Variable Elimination with Arbitrary Constraints. - Nima Taghipour; Daan Fierens; Jesse Davis; Hendrik Blockeel (AISTATS, 2012)

On the Completeness of Lifted Variable Elimination. - Nima Taghipour; Daan Fierens; Guy Van den Broeck; Jesse Davis; Hendrik Blockeel (StarAI@AAAI, 2013)

Completeness Results for Lifted Variable Elimination. - Nima Taghipour; Daan Fierens; Guy Van den Broeck; Jesse Davis; Hendrik Blockeel (AISTATS, 2013)

Lifted Variable Elimination: Decoupling the Operators from the Constraint Language. - Nima Taghipour; Daan Fierens; Jesse Davis; Hendrik Blockeel (J. Artif. Intell. Res., 2013)

Inference and learning in probabilistic logic programs using weighted Boolean formulas. - Daan Fierens; Guy Van den Broeck; Joris Renkens; Dimitar Sht. Shterionov; Bernd Gutmann; Ingo Thon; Gerda Janssens; Luc De Raedt (Theory Pract. Log. Program., 2015)

Instance-level accuracy versus bag-level accuracy in multi-instance learning. - Gitte Vanwinckelen; Vinicius Tragante do Ó; Daan Fierens; Hendrik Blockeel (Data Min. Knowl. Discov., 2016)