Luc De Raedt

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Advanced AI Techniques I. Bayesian Networks / 3. Structure Learning (2/3)

Wolfram Burgard, Luc De Raedt, Bernhard Nebel, 2004 .

Modeling in MiningZinc

Luc De Raedt, Anton Dries, Tias Guns, 2016, Data Mining and Constraint Programming.

Inductive Querying for Discovering Subgroups and Clusters

Luc De Raedt, Albrecht Zimmermann, L. D. Raedt, 2004, Constraint-Based Mining and Inductive Databases.

Declarative Modeling for Machine Learning and Data Mining

Luc De Raedt, 2012, Discovery Science.

Discovering Textual Structures: Generative Grammar Induction using Template Trees pdf

Luc De Raedt, Thomas Winters, 2020, ICCC.

Isidd: An Interactive System for Inductive Database Design

Luc De Raedt, Hendrik Blockeel, 1998, Appl. Artif. Intell..

Combining video and sequential statistical relational techniques to monitor card games

Luc De Raedt, Kristian Kersting, Laura Antanas, 2010, ICML 2010.

A Perspective on Inductive Logic Programming

Luc De Raedt, L. D. Raedt, 1999, The Logic Programming Paradigm.

Top-down induction of logical decision trees

Luc De Raedt, Hendrik Blockeel, L. D. Raedt, 1997 .

Applications of Probabilistic Logic Programming

Luc De Raedt, 2015, ILP 2015.

Wanted: association rules over multiple relations

Luc De Raedt, Luc Dehaspe, 1997 .

Constraint programming for correlated itemset mining

Luc De Raedt, Tias Guns, Siegfried Nijssen, 2009 .

Guest editorial to the special issue on inductive logic programming, mining and learning in graphs and statistical relational learning

Luc De Raedt, Kristian Kersting, Pedro M. Domingos, 2010, Machine Learning.

Predicting spike activity in neuronal cultures

Luc De Raedt, Stefan Rotter, Tayfun Gürel, 2007, 2007 International Joint Conference on Neural Networks.

Learning Relational Navigation Policies

Wolfram Burgard, Luc De Raedt, Kristian Kersting, 2006, 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems.

Probabilistic Logic Programs and Their Applications

Luc De Raedt, L. D. Raedt, 2016 .

Relational Learning and Inductive Logic Programming Made Easy Abstract of Tutorial

Luc De Raedt, Hendrik Blockeel, 1999, PKDD.

08041 Abstracts Collection -- Recurrent Neural Networks - Models, Capacities, and Applications

Luc De Raedt, Pascal Hitzler, Barbara Hammer, 2008, Recurrent Neural Networks.

Constraint programming for itemset mining

Luc De Raedt, Tias Guns, Siegfried Nijssen, 2008, KDD.

Probabilistic local pattern mining

Luc De Raedt, Angelika Kimmig, 2008 .

Active Learning for High Throughput Screening

Luc De Raedt, Jan Ramon, Kurt De Grave, 2008, Discovery Science.

Biography and future challenges

Luc De Raedt, Ivan Bratko, Stephen Muggleton, 2011 .

Declarative machine learning and data mining

Luc De Raedt, 2015 .

07161 Abstracts Collection -- Probabilistic, Logical and Relational Learning - A Further Synthesis

Luc De Raedt, Thomas G. Dietterich, Kristian Kersting, 2007, Probabilistic, Logical and Relational Learning - A Further Synthesis.

Grammar Mining

Luc De Raedt, Siegfried Nijssen, L. D. Raedt, 2009, SDM.

The Upgrading Story

Luc De Raedt, 2008 .

An introduction to hybrid probabilistic (logic) programming

Luc De Raedt, 2015, IJCAI 2015.

Statistical Relational Learning using ProbLog

Luc De Raedt, 2013, KNOW@LOD.

Learning Constraint Satisfaction Problems: An ILP Perspective

Luc De Raedt, Christian Bessiere, Anton Dries, 2016, Data Mining and Constraint Programming.

There are plenty of places like home: Using relational representations in hierarchies for distance-based image understanding

Luc De Raedt, Tinne Tuytelaars, Laura Antanas, 2014, Neurocomputing.

Declarative Modeling for Machine Learning and Data Mining

Luc De Raedt, 2012, ECML/PKDD.

A Simple Model for Sequences of Relational State Descriptions

Luc De Raedt, Ingo Thon, Niels Landwehr, 2008, ECML/PKDD.

A Logical Database Mining Query Language

Luc De Raedt, L. D. Raedt, 2000, ILP.

Three Companions for First Order Data Mining

Luc De Raedt, Wim Van Laer, Hendrik Blockeel, 1998 .

Introduction to the special issue on probability, logic and learning

Luc De Raedt, James Cussens, Taisuke Sato, 2015, Theory Pract. Log. Program..

Symbolic Learning and Reasoning With Noisy Data for Probabilistic Anchoring

Luc De Raedt, Amy Loutfi, Kumar Nitesh, 2020, Frontiers in Robotics and AI.

Condition Monitoring with Incomplete Observations

Luc De Raedt, Wannes Meert, Rocco Langone, 2014, ECAI.

Automated design of deductive databases

Luc De Raedt, Hendrik Blockeel, 1995 .

Explanation Based Program Transformation

Luc De Raedt, Maurice Bruynooghe, Danny De Schreye, 1989, IJCAI.

Relational Reinforcement Learning

Luc De Raedt, Saso Dzeroski, Kurt Driessens, 2001, Machine Learning.

Probabilistic (logic) programming concepts

Luc De Raedt, Angelika Kimmig, L. D. Raedt, 2015, Machine Learning.

A Brief Introduction to Inductive Logic Programming

Luc De Raedt, L. D. Raedt, 1993, ILPS.

Evaluating Pattern Set Mining Strategies in a Constraint Programming Framework

Luc De Raedt, Tias Guns, Siegfried Nijssen, 2011, PAKDD.

Logic, Probability and Learning, or an Introduction to Statistical Relational Learning

Luc De Raedt, 2008, SBIA.

Probabilistic Inductive Querying Using ProbLog

Luc De Raedt, Kristian Kersting, Hannu Toivonen, 2010, Inductive Databases and Constraint-Based Data Mining.

Approaches and Applications of Inductive Programming (Dagstuhl Seminar 19202)

Luc De Raedt, Richard Evans, Ute Schmid, 2019, Dagstuhl Reports.

ProbLog2: From probabilistic programming to statistical relational learning

Luc De Raedt, Guy Van den Broeck, Wannes Meert, 2012, NIPS 2012.

Probabilistic Logic Learning - A Tutorial Abstract

Luc De Raedt, L. D. Raedt, 2009, ICLP.

Spatial relation extraction using relational learning

Luc De Raedt, Marie-Francine Moens, Parisa Kordjamshidi, 2011, ILP 2011.

Towards digesting the alphabet-soup of statistical relational learning

Luc De Raedt, Wannes Meert, Bart Demoen, 2008 .

Transforming Probabilistic Programs into Algebraic Circuits for Inference and Learning

Luc De Raedt, Wannes Meert, Angelika Kimmig, 2019 .

Generality and Logical Entailment

Luc De Raedt, L. D. Raedt, 2008 .

Recent advances in lifted inference at Leuven

Luc De Raedt, Guy Van den Broeck, Wannes Meert, 2012 .

Constraint Based Mining of First Order Sequences in SeqLog

Luc De Raedt, Sau Dan Lee, L. D. Raedt, 2004, Database Support for Data Mining Applications.

05051 Executive Summary - Probabilistic, Logical and Relational Learning - Towards a Synthesis

Luc De Raedt, Thomas G. Dietterich, Stephen Muggleton, 2005, Probabilistic, Logical and Relational Learning.

I. Bayesian Networks / 4. Constrained-based Structure Learning (1/2)

Wolfram Burgard, Luc De Raedt, Bernhard Nebel, 2005 .

A probabilistic Prolog and its applications to link discovery in biological network mining

Luc De Raedt, 2007 .

Semantic and geometric reasoning for robotic grasping: a probabilistic logic approach

Luc De Raedt, Kristian Kersting, Plinio Moreno, 2018, Autonomous Robots.

Statistical Relational Learning of Object Affordances for Robotic Manipulation

Luc De Raedt, Plinio Moreno, José Santos-Victor, 2011, ILP.

Probabilistic programming (IJCAI tutorial)

Luc De Raedt, Angelika Kimmig, 2015 .

A unifying framework for concept-learning algorithms

Luc De Raedt, Maurice Bruynooghe, L. D. Raedt, 1992, The Knowledge Engineering Review.

Computational reasoning on high-throughput omics results using interaction networks

Luc De Raedt, Dries De Maeyer, Kathleen Marchal, 2015 .

Inductive Logic Programming

Luc De Raedt, L. D. Raedt, 2015, Lecture Notes in Computer Science.

Algebraic model counting

Luc De Raedt, Guy Van den Broeck, Angelika Kimmig, 2012, J. Appl. Log..

MiningZinc: A Modeling Language for Constraint-Based Mining

Luc De Raedt, Anton Dries, Tias Guns, 2013, IJCAI.

Inducing Probabilistic Relational Rules from Probabilistic Examples

Luc De Raedt, Guy Van den Broeck, Anton Dries, 2015, IJCAI.

Patterns and Logic for Reasoning with Networks

Luc De Raedt, Hannu Toivonen, Esther Galbrun, 2012, Bisociative Knowledge Discovery.

Statistical Relational Learning

Luc De Raedt, Kristian Kersting, 2010, Encyclopedia of Machine Learning.

How to Exploit Structure while Solving Weighted Model Integration Problems

Luc De Raedt, Samuel Kolb, Pedro Zuidberg Dos Martires, 2019, UAI.

Logical Settings for Concept-Learning

Luc De Raedt, L. D. Raedt, 1997, Artif. Intell..

On explanation and bias in inductive concept-learning

Luc De Raedt, Maurice Bruynooghe, 1989 .

The Inductive Constraint Programming Loop: Extended Abstract

Luc De Raedt, Barry O'Sullivan, Dino Pedreschi, 2016 .

ProbLog and its Application to Link Mining in Biological Networks

Luc De Raedt, 2007, MLG.

The Inductive Constraint Programming Loop

Luc De Raedt, Barry O'Sullivan, Dino Pedreschi, 2015, IEEE Intelligent Systems.

The pywmi Framework and Toolbox for Probabilistic Inference using Weighted Model Integration

Luc De Raedt, Paolo Morettin, Samuel Kolb, 2019, IJCAI.

PageRank, ProPPR, and Stochastic Logic Programs

Luc De Raedt, Angelika Kimmig, Dries Van Daele, 2014, ILP.

Logical and Relational Learning: From ILP to MRDM (Cognitive Technologies)

Luc De Raedt, L. D. Raedt, 2008 .

Bellman goes relational

Luc De Raedt, Kristian Kersting, Martijn van Otterlo, 2004, ICML.

Relational data factorization

Luc De Raedt, Sergey Paramonov, Matthijs van Leeuwen, 2017, Machine Learning.

Answering complex questions in natural language using probabilistic logic programming and the web

Luc De Raedt, José Antonio Oramas Mogrovejo, L. D. Raedt, 2010 .

Probabilistic Inductive Logic Programming

Luc De Raedt, Kristian Kersting, K. Kersting, 2004, Probabilistic Inductive Logic Programming.

Solving Probability Problems in Natural Language

Luc De Raedt, Jesse Davis, Anton Dries, 2017, IJCAI.

The inductive logic programming project

Luc De Raedt, L. D. Raedt, 1996 .

Application of Dynamic Distributional Clauses for multi-hypothesis initialization in model-based object tracking

Luc De Raedt, Georgios Chliveros, Maria Pateraki, 2015, 2014 International Conference on Computer Vision Theory and Applications (VISAPP).

On probability, rules and learning

Luc De Raedt, L. D. Raedt, 2014 .

Introduction to the Special Issue on the ECAI 2012 Turing and Anniversary Track

Luc De Raedt, Maria Fox, 2014, AI Commun..

Compiling probabilistic logic programs into sentential decision diagrams

Luc De Raedt, Guy Van den Broeck, Jonas Vlasselaer, 2014 .

Learning relational affordance models for robots in multi-object manipulation tasks

Luc De Raedt, Plinio Moreno, José Santos-Victor, 2012, 2012 IEEE International Conference on Robotics and Automation.

Itemset mining: A constraint programming perspective

Luc De Raedt, Tias Guns, Siegfried Nijssen, 2011, Artif. Intell..

Constraints, Optimization and Data (Dagstuhl Seminar 14411)

Luc De Raedt, Barry O'Sullivan, Siegfried Nijssen, 2014, Dagstuhl Reports.

Simultaneous discovery of cancer subtypes and subtype features by molecular data integration

Luc De Raedt, Dries De Maeyer, Kathleen Marchal, 2016, Bioinform..

Algebraic Circuits for Decision Theoretic Inference and Learning

Luc De Raedt, Vincent Derkinderen, 2020, ECAI.

Lazy Explanation-Based Approximation for Probabilistic Logic Programming pdf

Luc De Raedt, Angelika Kimmig, Joris Renkens, 2015, ArXiv.

Inverse Resolution in an Integrated Inductive-Deductive Learning System

Luc De Raedt, Maurice Bruynooghe, Hilde Adé, 1992, ECAI.

On the implementation of the probabilistic logic programming language ProbLog

Luc De Raedt, Bart Demoen, Ricardo Rocha, 2010, Theory and Practice of Logic Programming.

Condensed Representations for Inductive Logic Programming

Luc De Raedt, Jan Ramon, L. D. Raedt, 2004, KR.

08041 Summary -- Recurrent Neural Networks - Models, Capacities, and Applications

Luc De Raedt, Pascal Hitzler, Barbara Hammer, 2008, Recurrent Neural Networks.

Declarative Heuristic Search for Pattern Set Mining

Luc De Raedt, Tias Guns, Siegfried Nijssen, 2011, 2011 IEEE 11th International Conference on Data Mining Workshops.

Ensemble Learning for Relational Data

Luc De Raedt, Ryan A. Rossi, Hoda Eldardiry, 2020, J. Mach. Learn. Res..

Exact and Approximate Weighted Model Integration with Probability Density Functions Using Knowledge Compilation

Luc De Raedt, Anton Dries, Pedro Zuidberg Dos Martires, 2019, AAAI.

From Statistical Relational to Neuro-Symbolic Artificial Intelligence

Luc De Raedt, Sebastijan Dumancic, Giuseppe Marra, 2020, IJCAI.

Learning probabilistic relational models from sequential video data with applications in table-top and card games

Luc De Raedt, Laura Antanas, Ingo Thon, 2009 .

AI Research in the Benelux - Guest Editorial

Luc De Raedt, Han La Poutré, Floor Verdenius, 2000, AI Commun..

Analysis and Prediction of Piano Performances Using Inductive Logic Programming

Luc De Raedt, Erika Van Baelen, L. D. Raedt, 1996, Inductive Logic Programming Workshop.

Constructive Induction by Analogy

Luc De Raedt, Maurice Bruynooghe, 1989, ML.

Relational Learning and Inductive Logic Programming Made Easy Abstract of Tutorial

Luc De Raedt, Hendrik Blockeel, L. D. Raedt, 1999, PKDD.

Relational Symbol Grounding through Affordance Learning: An Overview of the ReGround Project

Luc De Raedt, Alessandro Saffiotti, Deniz Yuret, 2017 .

Towards Query Evaluation in Inductive Databases Using Version Spaces

Luc De Raedt, L. D. Raedt, 2004, Database Support for Data Mining Applications.

The functional components of concept-acquisition systems

Luc De Raedt, Maurice Bruynooghe, Bruno Krekels, 1987 .

Learning the Structure of Dynamic Hybrid Relational Models

Luc De Raedt, Jesse Davis, Irma Ravkic, 2016, ECAI.

nFOIL: Integrating Naïve Bayes and FOIL

Luc De Raedt, Kristian Kersting, Niels Landwehr, 2005, AAAI.

Probabilistic inductive logic programming

Luc De Raedt, Kristian Kersting, K. Kersting, 2004 .

Inductive Logic Programming

Luc De Raedt, L. D. Raedt, 2010, Encyclopedia of Machine Learning.

Proceedings of the 2004 European conference on Constraint-Based Mining and Inductive Databases

Luc De Raedt, Jean-François Boulicaut, Heikki Mannila, 2004 .

Under Consideration for Publication in Theory and Practice of Logic Programming the Magic of Logical Inference in Probabilistic Programming pdf

Luc De Raedt, Maurice Bruynooghe, Bernd Gutmann, 2022 .

Scaling Up Inductive Logic Programming by Learning from Interpretations

Luc De Raedt, Bart Demoen, Hendrik Blockeel, 1999, Data Mining and Knowledge Discovery.

CLINT : a multi-strategy interactive concept-learner and theory revision system

Luc De Raedt, Maurice Bruynooghe, L. D. Raedt, 1991 .

Efficient Probabilistic Inference for Dynamic Relational Models

Luc De Raedt, Guy Van den Broeck, Wannes Meert, 2014, StarAI@AAAI.

05051 Abstracts Collection - Probabilistic, Logical and Relational Learning - Towards a Synthesis

Luc De Raedt, Thomas G. Dietterich, Stephen Muggleton, 2005, Probabilistic, Logical and Relational Learning.

Machine Learning: ECML 2001

Luc De Raedt, Peter A. Flach, L. D. Raedt, 2001, Lecture Notes in Computer Science.

Active Preference Learning for Ranking Patterns

Luc De Raedt, Siegfried Nijssen, Matthijs van Leeuwen, 2013, 2013 IEEE 25th International Conference on Tools with Artificial Intelligence.

Proceedings of the 20th European Conference on Artificial Intelligence

Luc De Raedt, Didier Dubois, Christian Bessiere, 2012 .

Multi-class problems and discretization in ICL

Luc De Raedt, Saso Dzeroski, Wim Van Laer, 1996 .

Inductive verification and validation of multi agent systems

Luc De Raedt, Kurt Driessens, Nico Jacobs, 1998, EUROVAV.

Extending ProbLog with Continuous Distributions

Luc De Raedt, Manfred Jaeger, Bernd Gutmann, 2010, ILP.

Indirect relevance and bias in inductive concept-learning

Luc De Raedt, Maurice Bruynooghe, L. D. Raedt, 1990 .

The molecular feature miner MolFea

Luc De Raedt, Stefan Kramer, Christoph Helma, 2003 .

Automating Personnel Rostering by Learning Constraints Using Tensors

Luc De Raedt, Mohit Kumar, Stefano Teso, 2018, 2019 IEEE 31st International Conference on Tools with Artificial Intelligence (ICTAI).

Interaction networks to analyze gene lists from omics data

Luc De Raedt, Dries De Maeyer, Kathleen Marchal, 2013 .

MacCLINT: an interactive machine learning system

Luc De Raedt, Maurice Bruynooghe, Yves D. Willems, 1992 .

Statistical Relational Learning - A Logical Approach (Abstract of Invited Talk)

Luc De Raedt, 2007, NeSy.

MCMC Estimation of Conditional Probabilities in Probabilistic Programming Languages

Luc De Raedt, Jesse Davis, Ingo Thon, 2013, ECSQARU.

Declarative Bias for Specific-to-General ILP Systems

Luc De Raedt, Maurice Bruynooghe, Hilde Adé, 1994, Machine Learning.

Learning constraints in spreadsheets and tabular data

Luc De Raedt, Samuel Kolb, Tias Guns, 2017, Machine Learning.

Relational Kernel-Based Grasping with Numerical Features

Luc De Raedt, Plinio Moreno, Laura Antanas, 2015, ILP.

kProbLog: An Algebraic Prolog for Kernel Programming

Luc De Raedt, Paolo Frasconi, Francesco Orsini, 2015, ILP.

Interactive concept-learning

Luc De Raedt, L. D. Raedt, 1991 .

Learning SMT(LRA) Constraints using SMT Solvers

Luc De Raedt, Andrea Passerini, Samuel Kolb, 2018, IJCAI.

Bottom-up generalisation in inductive logic programming

Luc De Raedt, Hilde Adé, C Rouveirol, 1993 .

Logical Markov Decision Programs

Luc De Raedt, Kristian Kersting, K. Kersting, 2003 .

ProbAnch: a Modular Probabilistic Anchoring Framework

Luc De Raedt, Amy Loutfi, Andreas Persson, 2020, IJCAI.

Learning Machines - An Introduction

Luc De Raedt, L. D. Raedt, 2016 .

Towards practical inductive logic programming

Luc De Raedt, 2000 .

A hybrid approach to learning and its knowledge representation

Luc De Raedt, Maurice Bruynooghe, Marc Denecker, 1990 .

Inductive constraint logic and the mutagenesis problem

Luc De Raedt, Wim Van Laer, Hendrik Blockeel, 1995 .

PheNetic: network-based interpretation of molecular profiling data

Luc De Raedt, Dries De Maeyer, Kathleen Marchal, 2015, Nucleic Acids Res..

Luc De Raedt, Tias Guns, Siegfried Nijssen, 2009, KDD.

Using Shapiro's model inference system for concept learning

Luc De Raedt, Maurice Bruynooghe, Bruno Krekels, 1987 .

Inductive Logic Programming

Luc De Raedt, L. D. Raedt, 2010, Encyclopedia of Machine Learning.

Probabilistic, Logical and Relational Learning - A Further Synthesis, 15.04. - 20.04.2007

Luc De Raedt, Thomas G. Dietterich, Kristian Kersting, 2008, Probabilistic, Logical and Relational Learning - A Further Synthesis.

Probabilistic Prolog systems

Luc De Raedt, Vítor Santos Costa, Angelika Kimmig, 2011 .

Advances in Mining Graphs, Trees and Sequences

Luc De Raedt, Takashi Washio, Joost N. Kok, 2005, Fundam. Informaticae.

Learning MAX-SAT from Contextual Examples for Combinatorial Optimisation

Luc De Raedt, Samuel Kolb, Stefano Teso, 2020, AAAI.

Constraint-Based Pattern Set Mining

Luc De Raedt, Albrecht Zimmermann, L. D. Raedt, 2007, SDM.

Correlated itemset mining in ROC space

Luc De Raedt, Tias Guns, Siegfried Nijssen, 2009, KDD 2009.

Acquiring Object-Knowledge for Learning Systems

Luc De Raedt, Maurice Bruynooghe, Johan Feyaerts, 1991, EWSL.

Mining Predictive k-CNF Expressions

Luc De Raedt, Anton Dries, Siegfried Nijssen, 2010, IEEE Transactions on Knowledge and Data Engineering.

Anytime Inference in Probabilistic Logic Programs with Tp-Compilation

Luc De Raedt, Guy Van den Broeck, Wannes Meert, 2015, IJCAI.

Semiring Programming: A Declarative Framework for Generalized Sum Product Problems.

Luc De Raedt, Vaishak Belle, L. D. Raedt, 2016, 1609.06954.

Statistical relational learning for vision, robotics and natural language processing

Luc De Raedt, 2014 .

Towards synthesising inductive data models

Luc De Raedt, 2016 .

An overview of the interactive concept-learner and theory revisor CLINT

Luc De Raedt, Maurice Bruynooghe, 1992 .

Languages for Mining and Learning

Luc De Raedt, 2015, IJCAI 2015.

Representations for Mining and Learning

Luc De Raedt, 2008 .

An Efficient Algorithm for Mining String Databases Under Constraints

Luc De Raedt, Sau Dan Lee, L. D. Raedt, 2004, KDID.

Probabilistic (Logic) Programming: Concepts and Applications

Luc De Raedt, 2016 .

A brief overview of logic programming research at the K.U.Leuven, with notes on its industrialrelevance

Luc De Raedt, Gerda Janssens, Maurice Bruynooghe, 1996 .

Inductive logic programming and scientific discovery

Luc De Raedt, L. D. Raedt, 1995 .

Inductive Logic Programming: Theory and Methods

Luc De Raedt, Stephen Muggleton, S. Muggleton, 1994, J. Log. Program..

Relational affordances for multiple-object manipulation

Luc De Raedt, Plinio Moreno, José Santos-Victor, 2017, Autonomous Robots.

PageRank, ProPPR, and Stochastic Logic Programs

Luc De Raedt, Angelika Kimmig, Dries Van Daele, 2014, ILP.

Belief Updating from Integrity Constraints and Queries

Luc De Raedt, Maurice Bruynooghe, L. D. Raedt, 1992, Artif. Intell..

kLog: A Language for Logical and Relational Learning with Kernels (Extended Abstract)

Luc De Raedt, Paolo Frasconi, Fabrizio Costa, 2012, IJCAI.

Substitutions and refinement operators for PCNF

Luc De Raedt, Wim Van Laer, Shan-Hwei Nienhuys-Cheng, 1998 .

Towards Discovering Structural Signatures of Protein Folds Based on Logical Hidden Markov Models

Luc De Raedt, Tapani Raiko, Kristian Kersting, 2003, Pacific Symposium on Biocomputing.

A particle filter for probabilistic dynamic relational domains

Luc De Raedt, Guy Van den Broeck, Ingo Thon, 2012 .

Proceedings of the European conference on machine learning on Machine Learning

Luc De Raedt, Francesco Bergadano, 1994 .

Statistical Relational Learning: An Inductive Logic Programming Perspective

Luc De Raedt, 2005, PKDD.

Rank Matrix Factorisation

Luc De Raedt, Siegfried Nijssen, Thanh Le Van, 2015, PAKDD.

Machine learning for constraint acquisition

Luc De Raedt, L. D. Raedt, 2014 .

Neural probabilistic logic programming in DeepProbLog

Luc De Raedt, Sebastijan Dumancic, Angelika Kimmig, 2019, Artif. Intell..

Induction, Logic and Natural Language Processing

Luc De Raedt, Luc Dehaspe, 1994 .

Theta-Subsumption for Structural Matching

Luc De Raedt, Gunther Sablon, Peter Idestam-Almquist, 1997, ECML.

Context-based object viewpoint estimation: A 2D relational approach pdf

Luc De Raedt, Tinne Tuytelaars, M. JoséOramas, 2017, Comput. Vis. Image Underst..

Logical and relational learning

Luc De Raedt, L. D. Raedt, 2008, Cognitive Technologies.

Some Thoughts on inverse resolution

Luc De Raedt, Maurice Bruynooghe, Gunther Sablon, 1991 .

Not far away from home: A relational distance-based approach to understand images of houses

Luc De Raedt, Tinne Tuytelaars, Laura Antanas, 2011 .

Parallel inductive logic programming

Luc De Raedt, Luc Dehaspe, 1995 .

Languages for Learning and Mining

Luc De Raedt, L. D. Raedt, 2015, AAAI.

ECAI 2012 : 20th European Conference on Artificial Intelligence, 27-31 August 2012, Montpellier, France : including Prestigious Applications of Artificial Intelligence (PAIS-2012) System Demonstrations Track : proceedings

Luc De Raedt, 2012 .

Probabilistic and logical inference for network mining

Luc De Raedt, 2009 .

Proceedings of the 5th European Conference on Principles of Data Mining and Knowledge Discovery

Luc De Raedt, Arno Siebes, 2001 .

An Algebraic Prolog for Reasoning about Possible Worlds

Luc De Raedt, Guy Van den Broeck, Angelika Kimmig, 2011, AAAI.

Exploiting local and repeated structure in Dynamic Bayesian Networks

Luc De Raedt, Guy Van den Broeck, Wannes Meert, 2016, Artif. Intell..

Occluded object search by relational affordances

Luc De Raedt, Bogdan Moldovan, 2014, 2014 IEEE International Conference on Robotics and Automation (ICRA).

r-grams: Relational Grams

Luc De Raedt, Niels Landwehr, 2007, IJCAI.

Probabilistic Inductive Logic Programming

Luc De Raedt, Kristian Kersting, 2004, ALT.

Relational Sequence Learning

Luc De Raedt, Kristian Kersting, Bernd Gutmann, 2008, Probabilistic Inductive Logic Programming.

MiningZinc: A declarative framework for constraint-based mining

Luc De Raedt, Anton Dries, Tias Guns, 2017, Artif. Intell..

Relational regularization and feature ranking

Luc De Raedt, Fabrizio Costa, Mathias Verbeke, 2014, SDM 2014.

Towards Friendly Concept-Learners

Luc De Raedt, Maurice Bruynooghe, L. D. Raedt, 1989, IJCAI.

Machine Learning, Proceedings of the Twenty-Second International Conference (ICML 2005), Bonn, Germany, August 7-11, 2005

Luc De Raedt, Stefan Wrobel, L. D. Raedt, 2005, ICML.

Towards cautious collective inference for object verification

Luc De Raedt, Tinne Tuytelaars, M. JoséOramas, 2014, IEEE Winter Conference on Applications of Computer Vision.

Probabilistic logic programming for hybrid relational domains

Luc De Raedt, Tinne De Laet, Davide Nitti, 2016, Machine Learning.

Unifying intensional knowledge base updating and incremental concept-learning. or belief updatingfrom integrity constraints and queries

Luc De Raedt, Maurice Bruynooghe, 1990 .

A relational kernel-based approach to scene classification

Luc De Raedt, Paolo Frasconi, Tinne Tuytelaars, 2013, 2013 IEEE Workshop on Applications of Computer Vision (WACV).

Learning from satisfiability

Luc De Raedt, Luc Dehaspe, L. D. Raedt, 1997 .

Multi-Relational Data Mining

Luc De Raedt, 2010, Encyclopedia of Machine Learning.

A perspective on inductive databases

Luc De Raedt, L. D. Raedt, 2002, SKDD.

On the Efficient Execution of ProbLog Programs

Luc De Raedt, Bart Demoen, Ricardo Rocha, 2008, ICLP.

Statistical Relational Artificial Intelligence: Logic, Probability, and Computation

Luc De Raedt, Kristian Kersting, Sriraam Natarajan, 2016, Statistical Relational Artificial Intelligence.

Inductive Database Design

Luc De Raedt, Hendrik Blockeel, L. D. Raedt, 1996, ISMIS.

DLAB: a hypothesis space management tool

Luc De Raedt, Luc Dehaspe, L. D. Raedt, 1996 .

First-Order jk-Clausal Theories are PAC-Learnable

Luc De Raedt, Saso Dzeroski, L. D. Raedt, 1994, Artif. Intell..

Lazy and Eager Relational Learning Using Graph-Kernels

Luc De Raedt, Walter Daelemans, Mathias Verbeke, 2014, SLSP.

Parameter Learning in Probabilistic Databases: A Least Squares Approach

Luc De Raedt, Kristian Kersting, Bernd Gutmann, 2008, ECML/PKDD.

A Theory of Inductive Query Answering

Luc De Raedt, Heikki Mannila, Manfred Jaeger, 2010, Inductive Databases and Constraint-Based Data Mining.

Probabilistic Inductive Logic Programming - Theory and Applications

Luc De Raedt, Kristian Kersting, Stephen Muggleton, 2008, Probabilistic Inductive Logic Programming.

Ranking neurons for mining structure-activity relations in biological neural networks: NeuronRank

Luc De Raedt, Stefan Rotter, Tayfun Gürel, 2007, Neurocomputing.

DLAB - A declarative language bias for concept learning and knowledge discovery engines

Luc De Raedt, Luc Dehaspe, 1995 .

Reasoning about object relations for object pose classification

Luc De Raedt, Tinne Tuytelaars, José Antonio Oramas Mogrovejo, 2014 .

On Mining Closed Sets in Multi-Relational Data

Luc De Raedt, Gemma C. Garriga, Roni Khardon, 2007, IJCAI.

Exploring the efficacy of molecular fragments of different complexity in computational SAR modeling pdf

Luc De Raedt, Albrecht Zimmermann, Björn Bringmann, 2015, ArXiv.

Employing logical languages for image understanding

Luc De Raedt, Paolo Frasconi, Tinne Tuytelaars, 2011 .

An Introduction to Learning and Search

Luc De Raedt, 2008 .

Mining a natural language corpus for multi-relational association rules

Luc De Raedt, Luc Dehaspe, 1997 .

Semiring Rank Matrix Factorization

Luc De Raedt, Siegfried Nijssen, Thanh Le Van, 2017, IEEE Transactions on Knowledge and Data Engineering.

Probabilistic Programming Concepts pdf

Luc De Raedt, Angelika Kimmig, L. D. Raedt, 2013, ArXiv.

Constraint-Based Mining and Inductive Databases: European Workshop on Inductive Databases and Constraint Based Mining, Hinterzarten, Germany, March 11-13, ... / Lecture Notes in Artificial Intelligence)

Luc De Raedt, Jean-François Boulicaut, Heikki Mannila, 2006 .

Artificial Intelligence in Belgium and the BeNeLux: Past and Future

Luc De Raedt, 1997, AI Commun..

k-Pattern Set Mining under Constraints

Luc De Raedt, Tias Guns, Siegfried Nijssen, 2013, IEEE Transactions on Knowledge and Data Engineering.

Predictive spreadsheet autocompletion with constraints

Luc De Raedt, Samuel Kolb, Stefano Teso, 2019, Machine Learning.

ProbLog: A Probabilistic Prolog and its Application in Link Discovery

Luc De Raedt, Hannu Toivonen, Angelika Kimmig, 2007, IJCAI.

Towards Clausal Discovery for Stream Mining

Luc De Raedt, Anton Dries, L. D. Raedt, 2009, ILP.

Constraint-Based Querying for Bayesian Network Exploration

Luc De Raedt, Tias Guns, Siegfried Nijssen, 2015, IDA.

Stochastic relational processes: Efficient inference and applications

Luc De Raedt, Ingo Thon, Niels Landwehr, 2011, Machine Learning.

Inference and learning in probabilistic logic programs using weighted Boolean formulas

Luc De Raedt, Guy Van den Broeck, Dimitar Shterionov, 2013, Theory and Practice of Logic Programming.

Probabilistic programming and its applications

Luc De Raedt, 2015 .

Logic of Generality

Luc De Raedt, L. D. Raedt, 2010, Encyclopedia of Machine Learning.

"Omics" Result Interpretation Using Interaction Networks

Luc De Raedt, Kathleen Marchal, Bram Weytjens, 2013 .

ProbLog2: Probabilistic Logic Programming

Luc De Raedt, Guy Van den Broeck, Wannes Meert, 2015, ECML/PKDD.

TP-Compilation for inference in probabilistic logic programs

Luc De Raedt, Guy Van den Broeck, Wannes Meert, 2016, Int. J. Approx. Reason..

Data Mining as Constraint Logic Programming

Luc De Raedt, L. D. Raedt, 2002, Computational Logic: Logic Programming and Beyond.

Phase Transitions and Stochastic Local Search in k-Term DNF Learning

Luc De Raedt, Ulrich Rückert, Stefan Kramer, 2002, ECML.

A theory of inductive query answering

Luc De Raedt, Heikki Mannila, Manfred Jaeger, 2002, 2002 IEEE International Conference on Data Mining, 2002. Proceedings..

Kernel-Based Logical and Relational Learning with kLog for Hedge Cue Detection

Roser Morante, Luc De Raedt, Walter Daelemans, 2011, ILP.

Distributional Clauses Particle Filter

Luc De Raedt, Tinne De Laet, Davide Nitti, 2014, ECML/PKDD.

Constraint Programming for Data Mining and Machine Learning

Luc De Raedt, Tias Guns, Siegfried Nijssen, 2010, AAAI.

Qualitative Spatial Reasoning for Soccer Pass Prediction

Luc De Raedt, Vincent Vercruyssen, Jesse Davis, 2016, MLSA@PKDD/ECML.

kLogNLP: Graph Kernel–based Relational Learning of Natural Language

Luc De Raedt, Paolo Frasconi, Fabrizio Costa, 2014, ACL.

Proceedings of the 12th European Conference on Machine Learning

Luc De Raedt, Peter A. Flach, L. D. Raedt, 2001 .

Planning in Discrete and Continuous Markov Decision Processes by Probabilistic Programming

Luc De Raedt, Vaishak Belle, Davide Nitti, 2015, ECML/PKDD.

Probabilistic logic learning

Luc De Raedt, Kristian Kersting, K. Kersting, 2003, SKDD.

Relational Reinforcement Learning

Luc De Raedt, Saso Dzeroski, Hendrik Blockeel, 1998, ILP.

Probabilistic logic programming for robotics

Luc De Raedt, 2015 .

Forgetting and Compacting data in Concept Learning

Luc De Raedt, Gunther Sablon, 1995, IJCAI.

kProbLog: an algebraic Prolog for machine learning

Luc De Raedt, Paolo Frasconi, Francesco Orsini, 2017, Machine Learning.

Towards Automated Relational Data Wrangling

Luc De Raedt, Gust Verbruggen, L. D. Raedt, 2017, AutoML@PKDD/ECML.

Relational decomposition using Answer Set Programming

Luc De Raedt, Sergey Paramonov, Matthijs van Leeuwen, 2013, ILP 2013.

Relational Learning for Spatial Relation Extraction from Natural Language

Luc De Raedt, Marie-Francine Moens, Parisa Kordjamshidi, 2011, ILP.

Machine learning and data mining: challenges and opportunities for constraint programming (tutorial)

Luc De Raedt, Siegfried Nijssen, L. D. Raedt, 2011 .

DTProbLog: A Decision-Theoretic Probabilistic Prolog

Luc De Raedt, Guy Van den Broeck, Ingo Thon, 2010, AAAI.

Constraints for probabilistic logic programming

Luc De Raedt, Guy Van den Broeck, Maurice Bruynooghe, 2012, NIPS 2012.

Ordering Variables for Weighted Model Integration

Luc De Raedt, Samuel Kolb, Pedro Zuidberg Dos Martires, 2020, UAI.

Statistical relational learning: an inductive logic programming perspective

Luc De Raedt, 2005 .

Proceedings of the 22nd international conference on Machine learning

Luc De Raedt, Saso Dzeroski, Stefan Wrobel, 2005 .

Interactive Learning of Pattern Rankings

Luc De Raedt, Siegfried Nijssen, Matthijs van Leeuwen, 2014, Int. J. Artif. Intell. Tools.

An algebra for inductive query evaluation

Luc De Raedt, Sau Dan Lee, L. D. Raedt, 2003, Third IEEE International Conference on Data Mining.

Mining closed patterns in relational, graph and network data

Luc De Raedt, Gemma C. Garriga, Roni Khardon, 2013, Annals of Mathematics and Artificial Intelligence.

Compressing probabilistic Prolog programs

Luc De Raedt, Kate Revoredo, Kristian Kersting, 2007, Machine Learning.

Principles of Data Mining and Knowledge Discovery: 5th European Conference, PKDD 2001, Freiburg, Germany, September 3-5, 2001 Proceedings

Luc De Raedt, Arno Siebes, 2001 .

An experimental evaluation of simplicity in rule learning

Luc De Raedt, Ulrich Rückert, L. D. Raedt, 2008, Artif. Intell..

Relational Regularization and Feature Ranking

Luc De Raedt, Fabrizio Costa, Mathias Verbeke, 2014, SDM.

A query language for analyzing networks

Luc De Raedt, Anton Dries, Siegfried Nijssen, 2009, CIKM.

Scalable Rule Learning in Probabilistic Knowledge Bases

Luc De Raedt, Guy Van den Broeck, Ondrej Kuzelka, 2019, AKBC.

Kernels on Prolog Proof Trees: Statistical Learning in the ILP Setting

Luc De Raedt, Paolo Frasconi, Andrea Passerini, 2006, J. Mach. Learn. Res..

Automatic solver chaining in MiningZinc

Luc De Raedt, Anton Dries, Tias Guns, 2015 .

Neuronrank for mining structure-activity relationships of biological neural networks

Luc De Raedt, Stefan Rotter, Tayfun Gürel, 2006 .

Not Far Away from Home: A Relational Distance-Based Approach to Understanding Images of Houses

Luc De Raedt, Tinne Tuytelaars, Laura Antanas, 2010, ILP.

Expressivity Analysis for PL-Languages

Luc De Raedt, Kristian Kersting, Manfred Jaeger, 2006 .

Learning Playing Strategies from Chess Endgame Databases: An ILP Approach

Luc De Raedt, Johannes Fürnkranz, L. D. Raedt, 1997 .

Learning Constraints From Examples

Luc De Raedt, Andrea Passerini, Stefano Teso, 2018, AAAI.

Mining Structure-Activity Relations in Biological Neural Networks using NeuronRank

Luc De Raedt, Stefan Rotter, Tayfun Gürel, 2007, Perspectives of Neural-Symbolic Integration.

Inductive Verification and Validation of the KULRoT RoboCup Team

Luc De Raedt, Kurt Driessens, Nico Jacobs, 1998, RoboCup.

The Logic of Learning

Luc De Raedt, 2009, ICFCA.

Mining Bi-sets in Numerical Data

Luc De Raedt, Jean-François Boulicaut, Céline Robardet, 2006, KDID.

Flexible constrained sampling with guarantees for pattern mining

Luc De Raedt, Matthijs van Leeuwen, Vladimir Dzyuba, 2016, Data Mining and Knowledge Discovery.

Sketched Answer Set Programming

Luc De Raedt, Christian Bessiere, Anton Dries, 2017, 2018 IEEE 30th International Conference on Tools with Artificial Intelligence (ICTAI).

Relational transformation-based tagging for human activity recognition

Luc De Raedt, Matthai Philipose, Bernd Gutmann, 2007 .

A particle filter for hybrid relational domains

Luc De Raedt, Tinne De Laet, Davide Nitti, 2013, 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems.

Generalizing Refinement Operators to Learn Prenex Conjunctive Normal Forms

Luc De Raedt, Wim Van Laer, Jan Ramon, 1999, ILP.

Statistical Relational Learning

Luc De Raedt, Kristian Kersting, 2017, Encyclopedia of Machine Learning and Data Mining.

Constraint-Based Mining and Inductive Databases, European Workshop on Inductive Databases and Constraint Based Mining, Hinterzarten, Germany, March 11-13, 2004, Revised Selected Papers

Luc De Raedt, Heikki Mannila, Jean-François Boulicaut, 2005, Constraint-Based Mining and Inductive Databases.

The Levelwise Version Space Algorithm and its Application to Molecular Fragment Finding

Luc De Raedt, Stefan Kramer, L. D. Raedt, 2001, IJCAI.

Deriving distance metrics from generality relations

Luc De Raedt, Jan Ramon, L. D. Raedt, 2009, Pattern Recognit. Lett..

IQL: A Proposal for an Inductive Query Language

Luc De Raedt, Siegfried Nijssen, L. D. Raedt, 2006, KDID.

A probabilistic database and its application to biological link mining

Luc De Raedt, Hannu Toivonen, Angelika Kimmig, 2007 .

PheNetic: "Omics" Interpretation Using Interaction Networks

Luc De Raedt, Dries De Maeyer, Kathleen Marchal, 2014 .

Using and developing declarative languages for machine learning and data mining

Luc De Raedt, 2015, ICLP 2015.

Proceedings of the 19th international conference on Inductive logic programming

Luc De Raedt, L. D. Raedt, 2009 .

Using Logical Decision Trees for Clustering

Luc De Raedt, Hendrik Blockeel, L. D. Raedt, 1997, ILP.

Interactive concept-learning and constructive induction by analogy

Luc De Raedt, Maurice Bruynooghe, L. D. Raedt, 2004, Machine Learning.

Relational Transformation-based Tagging for Activity Recognition

Luc De Raedt, Matthai Philipose, Bernd Gutmann, 2008, Fundam. Informaticae.

On Multi-class Problems and Discretization in Inductive Logic Programming

Luc De Raedt, Saso Dzeroski, Wim Van Laer, 1997, ISMIS.

Instance Based Function Learning

Luc De Raedt, Jan Ramon, L. D. Raedt, 1999, ILP.

Planning in hybrid relational MDPs

Luc De Raedt, Vaishak Belle, Tinne De Laet, 2017, Machine Learning.

Logic of Generality

Luc De Raedt, L. D. Raedt, 2010, Encyclopedia of Machine Learning.

Molecular feature mining in HIV data

Luc De Raedt, Stefan Kramer, Christoph Helma, 2001, KDD '01.

Sample-based abstraction for hybrid relational MDPs

Luc De Raedt, Vaishak Belle, Tinne De Laet, 2015 .

Interactive theory revision

Luc De Raedt, Maurice Bruynooghe, L. D. Raedt, 1994 .

Frequent Hypergraph Mining

Luc De Raedt, Tamás Horváth, Björn Bringmann, 2006, ILP.

Relational Affordance Learning for Task-Dependent Robot Grasping

Luc De Raedt, Anton Dries, Plinio Moreno, 2017, ILP.

Benelearn: The First 10 Years

Luc De Raedt, Maarten van Someren, 2000, AI Commun..

Knowledge Compilation and Weighted Model Counting for Inference in Probabilistic Logic Programs

Luc De Raedt, Wannes Meert, Anton Dries, 2016, AAAI Workshop: Beyond NP.

Generalizing Multiple Examples in Explanation Based Learning

Luc De Raedt, Maurice Bruynooghe, Gunther Sablon, 1989, AII.

A Theory of Clausal Discovery

Luc De Raedt, Maurice Bruynooghe, L. D. Raedt, 1993, IJCAI.

Explanation-Based Approximate Weighted Model Counting for Probabilistic Logics

Luc De Raedt, Guy Van den Broeck, Angelika Kimmig, 2014, AAAI.

Cluster-grouping: from subgroup discovery to clustering

Luc De Raedt, Albrecht Zimmermann, L. D. Raedt, 2004, Machine Learning.

Inductive logic programming: an introduction

Luc De Raedt, L. D. Raedt, 1992 .

Constraint Programming for Data Mining

Luc De Raedt, 2009, EGC.

Panel: Logic and Learnability

Luc De Raedt, 1991, EWSL.

Machine Learning: Ecml-94 : European Conference on Machine Learning, Catania, Italy, April 6-8, 1994 : Proceedings

Luc De Raedt, Francesco Bergadano, 1994 .

Probabilistic programming (ECAI tutorial)

Luc De Raedt, Angelika Kimmig, L. D. Raedt, 2014 .

Probabilistic Programs and Their Applications

Luc De Raedt, L. D. Raedt, 2016 .

Editors' Introduction to the Special Issue on "Information and Communication Technology"

Luc De Raedt, Yves Deville, Marc Bui, 2017, Informatica.

Advances in Mining Graphs, Trees and Sequences: Preface

Luc De Raedt, Takashi Washio, Joost N. Kok, 2004 .

Automating Data Science (Dagstuhl Seminar 18401)

Luc De Raedt, Tijl De Bie, Padhraic Smyth, 2018, Dagstuhl Reports.

kFOIL: Learning Simple Relational Kernels

Luc De Raedt, Paolo Frasconi, Andrea Passerini, 2006, AAAI.

An Exercise in Declarative Modeling for Relational Query Mining

Luc De Raedt, Sergey Paramonov, Marc Denecker, 2015, ILP.

Learning Distributional Programs for Relational Autocompletion pdf

Luc De Raedt, Kumar Nitesh, Ondrej Kuzelka, 2020, ArXiv.

Machine Learning: EMCL 2001, 12th European Conference on Machine Learning, Freiburg, Germany, September 5-7, 2001, Proceedings

Luc De Raedt, Peter A. Flach, 2001, ECML.

Feature Construction with Version Spaces for Biochemical Applications

Luc De Raedt, Stefan Kramer, L. D. Raedt, 2001, ICML.

Using ILP-Systems for Verification and Validation of Multi-agent Systems

Luc De Raedt, Kurt Driessens, Nico Jacobs, 1998, ILP.

PAC-Learning Logic Programs under the Closed-World Assumption

Luc De Raedt, L. D. Raedt, 1996, ISMIS.

Top-Down Induction of Clustering Trees

Luc De Raedt, Jan Ramon, Hendrik Blockeel, 1998, ICML.

Proximity-based cis-regulatory module detection using constraint programming for itemset mining

Luc De Raedt, Kathleen Marchal, Hong Sun, 2010 .

Integrity Constraints and Interactive Concept-Learning

Luc De Raedt, Maurice Bruynooghe, Bern Martens, 1991, ML.

Probabilistic Rule Learning

Luc De Raedt, Ingo Thon, L. D. Raedt, 2010, ILP.

Inductive databases for bio- and chemoinformatics

Luc De Raedt, Stefan Kramer, L. D. Raedt, 2003 .

Don't Be Afraid of Simpler Patterns

Luc De Raedt, Siegfried Nijssen, Albrecht Zimmermann, 2006, PKDD.

Progress in probabilistic programming

Luc De Raedt, L. D. Raedt, 2014 .

Probabilistic, Logical and Relational Learning - Towards a Synthesis, 30. January - 4. February 2005

Luc De Raedt, Thomas G. Dietterich, Stephen Muggleton, 2006, Probabilistic, Logical and Relational Learning.

SynthLog: A Language for Synthesising Inductive Data Models (Extended Abstract)

Luc De Raedt, Samuel Kolb, Stefano Teso, 2019, PKDD/ECML Workshops.

Inductive Logic Programming, 19th International Conference, ILP 2009, Leuven, Belgium, July 02-04, 2009. Revised Papers

Luc De Raedt, 2010, ILP.

Using interactive concept learning for knowledge-base validation and verification

Luc De Raedt, Maurice Bruynooghe, Gunther Sablon, 1991 .

Inductive Logic Programming: A Survey of European Research

Luc De Raedt, Nada Lavrac, L. D. Raedt, 1995, AI Commun..

Acquiring Integer Programs from Data

Luc De Raedt, Mohit Kumar, Stefano Teso, 2019, IJCAI.

Integrating Naïve Bayes and FOIL

Luc De Raedt, Kristian Kersting, Niels Landwehr, 2007, J. Mach. Learn. Res..

Lifted Probabilistic Inference by First-Order Knowledge Compilation

Luc De Raedt, Guy Van den Broeck, Wannes Meert, 2011, IJCAI.

Neural-Symbolic Learning and Reasoning: Contributions and Challenges

Luc De Raedt, Risto Miikkulainen, Kai-Uwe Kühnberger, 2015, AAAI Spring Symposia.

I. Bayesian Networks / 3. Parameter Learning with Missing Values

Wolfram Burgard, Luc De Raedt, Bernhard Nebel, 2005 .

Iterative Versionspaces

Luc De Raedt, Maurice Bruynooghe, Gunther Sablon, 1994, Artif. Intell..

TaCLe: Learning Constraints in Tabular Data

Luc De Raedt, Samuel Kolb, Tias Guns, 2017, CIKM.

Predicting Spike Activity in Neuronal Cultures

Luc De Raedt, Stefan Rotter, Tayfun Gürel, 2007 .

Machine Learning for Verification and Validation

Luc De Raedt, L. D. Raedt, 1997, EUROVAV.

The MiningZinc Framework for Constraint-Based Itemset Mining

Luc De Raedt, Anton Dries, Tias Guns, 2013, 2013 IEEE 13th International Conference on Data Mining Workshops.

Probabilistic Explanation Based Learning

Luc De Raedt, Hannu Toivonen, Angelika Kimmig, 2007, ECML.

Proceedings of the Sixth International Symposium on Information and Communication Technology

Luc De Raedt, Yves Deville, Huynh Quyet Thang, 2015 .

Lifted inference for probabilistic programming

Luc De Raedt, Guy Van den Broeck, Wannes Meert, 2012, NIPS 2012.

Human-Machine Collaboration for Democratizing Data Science pdf

Luc De Raedt, Samuel Kolb, Stefano Teso, 2020, Human-Like Machine Intelligence.

Learning from Implicit Information in Natural Language Instructions for Robotic Manipulations pdf

Luc De Raedt, Alessandro Saffiotti, Deniz Yuret, 2019, ArXiv.

Machine Learning: ECML-94

Luc De Raedt, Francesco Bergadano, L. D. Raedt, 1994, Lecture Notes in Computer Science.

On Negation and Three-Valued Logic in Interactive Concept-Learning

Luc De Raedt, Maurice Bruynooghe, L. D. Raedt, 1990, ECAI.

Learning relational affordance models for two-arm robots

Luc De Raedt, Bogdan Moldovan, L. D. Raedt, 2014, 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems.

Multi-relational data mining: the current frontiers

Luc De Raedt, Saso Dzeroski, 2003, SKDD.

Computational Aspects of Logical and Relational Learning

Luc De Raedt, L. D. Raedt, 2008 .

Estimating the parameters of probabilistic databases from probabilistically weighted queries and proofs [extended abstract]

Luc De Raedt, Kristian Kersting, Bernd Gutmann, 2008 .

A Statistical Relational Learning Approach to Identifying Evidence Based Medicine Categories

Roser Morante, Luc De Raedt, Walter Daelemans, 2012, EMNLP.

10 Years of Probabilistic Querying - What Next?

Luc De Raedt, Martin Theobald, Iris Miliaraki, 2013, ADBIS.

Mechanistic interpretation of gene lists using interaction networks

Luc De Raedt, Dries De Maeyer, Kathleen Marchal, 2013 .

Relational object tracking and learning

Luc De Raedt, Tinne De Laet, Davide Nitti, 2014, 2014 IEEE International Conference on Robotics and Automation (ICRA).

Knowledge Compilation with Continuous Random Variables and its Application in Hybrid Probabilistic Logic Programming pdf

Luc De Raedt, Anton Dries, Pedro Zuidberg Dos Martires, 2018, ArXiv.

DLAB: A Declarative Language Bias Formalism

Luc De Raedt, Luc Dehaspe, 1996, ISMIS.

Multi-relational data mining: a workshop report

Luc De Raedt, Saso Dzeroski, 2002, SKDD.

Towards Combining Inductive Logic Programming with Bayesian Networks

Luc De Raedt, Kristian Kersting, K. Kersting, 2001, ILP.

Towards Learning Stochastic Logic Programs from Proof-Banks

Luc De Raedt, Kristian Kersting, Sunna Torge, 2005, AAAI.

Local Query Mining in a Probabilistic Prolog

Luc De Raedt, Angelika Kimmig, L. D. Raedt, 2009, IJCAI.

Adaptive Bayesian Logic Programs

Luc De Raedt, Kristian Kersting, K. Kersting, 2001, ILP.

Induction in logic

Luc De Raedt, L. D. Raedt, 1996 .

On the history and future of machine learning: A personal interpretation and perspective

Luc De Raedt, 2016 .

Logical and Relational Learning

Luc De Raedt, 2008, SBIA.

Inference in Probabilistic Logic Programs using Weighted CNF's

Luc De Raedt, Guy Van den Broeck, Bernd Gutmann, 2011, UAI.

Predictive Graph Mining

Luc De Raedt, Andreas Karwath, 2004, Discovery Science.

Can we automate data science

Luc De Raedt, L. D. Raedt, 2016 .

Acquiring object-knowledge

Luc De Raedt, Maurice Bruynooghe, Johan Feyaerts, 1992, J. Exp. Theor. Artif. Intell..

BiQL: A Query Language for Analyzing Information Networks

Luc De Raedt, Anton Dries, Siegfried Nijssen, 2012, Bisociative Knowledge Discovery.

Recurrent Neural Networks - Models, Capacities, and Applications, 20.01. - 25.01.2008

Luc De Raedt, Pascal Hitzler, Barbara Hammer, 2008, Recurrent Neural Networks.

Semiring programming: A semantic framework for generalized sum product problems

Luc De Raedt, Vaishak Belle, L. D. Raedt, 2020, Int. J. Approx. Reason..

Declarative Modeling for Machine Learning and Data Mining

Luc De Raedt, 2012, ALT.

Multi-relational Data Mining

Luc De Raedt, L. D. Raedt, 2010, Encyclopedia of Machine Learning and Data Mining.

Probabilistic logic programs: Unifying program trace and possible world semantics

Luc De Raedt, Angelika Kimmig, L. D. Raedt, 2017 .

CPT-L: An efficient model for relational stochastic processes

Luc De Raedt, Ingo Thon, Niels Landwehr, 2008 .

Elements of an Automatic Data Scientist

Luc De Raedt, Samuel Kolb, Hendrik Blockeel, 2018, IDA.

Features of concept learning: a generic algorithm

Luc De Raedt, Maurice Bruynooghe, L. D. Raedt, 1988 .

Luc De Raedt, Albrecht Zimmermann, L. D. Raedt, 2004, Discovery Science.

Bayesian Logic Programming: Theory and Tool

Luc De Raedt, Kristian Kersting, K. Kersting, 2007 .

SMIREP: Predicting Chemical Activity from SMILES

Luc De Raedt, Andreas Karwath, L. D. Raedt, 2006, J. Chem. Inf. Model..

Data Mining and Constraint Programming

Luc De Raedt, Barry O'Sullivan, Dino Pedreschi, 2016, Lecture Notes in Computer Science.

Logical Hidden Markov Models (Extendes abstract)

Luc De Raedt, Tapani Raiko, Kristian Kersting, 2002, Probabilistic Graphical Models.

Lookahead and Discretization in ILP

Luc De Raedt, Hendrik Blockeel, L. D. Raedt, 1997, ILP.

RUTH : an ILP approach to theory revision

Luc De Raedt, Hilde Adé, Bart Malfait, 1994 .

How to Upgrade Propositional Learners to First Order Logic: A Case Study

Luc De Raedt, Wim Van Laer, L. D. Raedt, 2001, Machine Learning and Its Applications.

Advanced AI Techniques I. Bayesian Networks / 1. Probabilistic Independence and Separation in Graphs

Wolfram Burgard, Luc De Raedt, Bernhard Nebel, 2005 .

ILP turns 20

Luc De Raedt, Katsumi Inoue, Ashwin Srinivasan, 2011, Machine Learning.

Constructive Induction by Analogy : a method to learn how to learn

Luc De Raedt, Maurice Bruynooghe, L. D. Raedt, 1989 .

Effective feature construction by maximum common subgraph sampling

Luc De Raedt, Jan Ramon, Fabrizio Costa, 2010, Machine Learning.

Kernels and Distances for Structured Data

Luc De Raedt, L. D. Raedt, 2008 .

About Knowledge and Inference in Logical and Relational Learning

Luc De Raedt, L. D. Raedt, 2010, Advances in Machine Learning II.

Multiple Predicate Learning

Luc De Raedt, Saso Dzeroski, Nada Lavrac, 1993, IJCAI.

Attribute-Value Learning Versus Inductive Logic Programming: The Missing Links (Extended Abstract)

Luc De Raedt, L. D. Raedt, 1998, ILP.

Declarative Modeling for Machine Learning and Data Mining

Luc De Raedt, 2012, ICFCA.

Cluster-Grouping: From Subgroup Discovery to Clustering

Luc De Raedt, Albrecht Zimmermann, 2004, ECML.

Fast learning of relational kernels

Luc De Raedt, Paolo Frasconi, Andrea Passerini, 2010, Machine Learning.

Online Proceedings of the Workshop on Statistical Relational Learning (SRL-06)

Luc De Raedt, Kristian Kersting, Manfred Jaeger, 2006 .

A clausal discovery engine

Luc De Raedt, Maurice Bruynooghe, 1992 .

Database Mining and Inductive Logic Programming

Luc De Raedt, L. D. Raedt, 1999, JFPLC.

Data Mining and Machine Learning Techniques for the Identification of Mutagenicity Inducing Substructures and Structure Activity Relationships of Noncongeneric Compounds

Luc De Raedt, Stefan Kramer, Christoph Helma, 2004, J. Chem. Inf. Model..

Towards Optimizing Conjunctive Inductive Queries

Luc De Raedt, Johannes Fischer, L. D. Raedt, 2004, KDID.

An Inductive Logic Programming Query Language for Database Mining

Luc De Raedt, L. D. Raedt, 1998, AISC.

Probabilistic logical sequence learning for video

Luc De Raedt, Laura Antanas, Ingo Thon, 2009, ILP 2009.

Mining Association Rules in Multiple Relations

Luc De Raedt, Luc Dehaspe, L. D. Raedt, 1997, ILP.

Revising Probabilistic Prolog Programs

Luc De Raedt, Kate Revoredo, Kristian Kersting, 2006, ILP.

Bayesian Logic Programs

Luc De Raedt, Kristian Kersting, K. Kersting, 2001, ILP Work-in-progress reports.

The Many Faces of Inductive Logic Programming

Luc De Raedt, Nada Lavrac, L. D. Raedt, 1993, ISMIS.

Applications of a Logical Discovery Engine

Luc De Raedt, Wim Van Laer, Luc Dehaspe, 1994, KDD Workshop.

Automatically Wrangling Spreadsheets into Machine Learning Data Formats

Luc De Raedt, Gust Verbruggen, L. D. Raedt, 2018, IDA.

On Interactive Concept-Learning and Assimilation

Luc De Raedt, Maurice Bruynooghe, 1988, EWSL.

Logic and learnability, abstract of a panel

Luc De Raedt, L. D. Raedt, 1991 .

High-level Reasoning and Low-level Learning for Grasping: A Probabilistic Logic Pipeline pdf

Luc De Raedt, Kristian Kersting, Plinio Moreno, 2014, ArXiv.

Multirelational data mining 2003: workshop report

Luc De Raedt, Saso Dzeroski, Stefan Wrobel, 2003, SKDD.

Parameter estimation in ProbLog from annotated queries

Luc De Raedt, Kristian Kersting, Bernd Gutmann, 2010 .

DeepProbLog: Neural Probabilistic Logic Programming

Luc De Raedt, Thomas Demeester, Sebastijan Dumancic, 2018, BNAIC/BENELEARN.

A Relational Kernel-Based Framework for Hierarchical Image Understanding

Luc De Raedt, Paolo Frasconi, Tinne Tuytelaars, 2012, SSPR/SPR.

The Machine Learning Revolution in AI

Luc De Raedt, L. D. Raedt, 2016 .

Constraint Programming meets Machine Learning and Data Mining (Dagstuhl Seminar 11201)

Luc De Raedt, Pascal Van Hentenryck, Barry O'Sullivan, 2011, Dagstuhl Reports.

Relational Knowledge Discovery in Databases

Luc De Raedt, Hendrik Blockeel, 1996, Inductive Logic Programming Workshop.

Towards clausal discovery for stream mining (extended abstract)

Luc De Raedt, Anton Dries, L. D. Raedt, 2009, International Conference on Inductive Logic Programming.

Introduction to Special issue on "The Sixth International Symposium on Information and Communication Technology -SoICT 2015

Luc De Raedt, Yves Deville, Marc Bui, 2016, Informatica.

Allocentric Pose Estimation

Luc De Raedt, Tinne Tuytelaars, M. JoséOramas, 2013, 2013 IEEE International Conference on Computer Vision.

Probabilistic programming: Concepts and challenges (extended abstract)

Luc De Raedt, Angelika Kimmig, 2014 .

A Relational Distance-based Framework for Hierarchical Image Understanding

Luc De Raedt, Tinne Tuytelaars, Laura Antanas, 2012, ICPRAM.

Mining Local Staircase Patterns in Noisy Data

Luc De Raedt, Kathleen Marchal, Tias Guns, 2012, 2012 IEEE 12th International Conference on Data Mining Workshops.

Towards declarative languages for learning

Luc De Raedt, L. D. Raedt, 2013 .

An Inductive Logic Programming Query Language for Database Mining (Extended Abstract)

Luc De Raedt, 1998 .

ProbLog Technology for Inference in a Probabilistic First Order Logic

Luc De Raedt, Gerda Janssens, Maurice Bruynooghe, 2010, ECAI.

Inductive Constraint Logic

Luc De Raedt, Wim Van Laer, L. D. Raedt, 1995, ALT.

RUTH: an ILP Theory Revision System

Luc De Raedt, Hilde Adé, Bart Malfait, 1994, ISMIS.

Learning the Parameters of Probabilistic Logic Programs from Interpretations

Luc De Raedt, Bernd Gutmann, Ingo Thon, 2011, ECML/PKDD.

CLASSIC'CL: An Integrated ILP System

Luc De Raedt, Christian Stolle, Andreas Karwath, 2005, Discovery Science.

Basic Principles of Learning Bayesian Logic Programs

Luc De Raedt, Kristian Kersting, K. Kersting, 2008, Probabilistic Inductive Logic Programming.

Clausal Discovery

Luc De Raedt, Luc Dehaspe, L. D. Raedt, 1997, Machine Learning.

The Clausal Discovery Engine User's Guide 3.0

Luc De Raedt, Wim Van Laer, Luc Dehaspe, 1996 .

Statistical relational learning: a logical approach

Luc De Raedt, 2007 .

Ranked Tiling

Luc De Raedt, Kathleen Marchal, Siegfried Nijssen, 2014, ECML/PKDD.

Multiple Predicate Learning in Two Inductive Logic Programming Settings

Luc De Raedt, Nada Lavrac, L. D. Raedt, 1996, Log. J. IGPL.

Towards Programming Languages for Machine Learning and Data Mining (Extended Abstract)

Luc De Raedt, Siegfried Nijssen, L. D. Raedt, 2011, ISMIS.

Graph Invariant Kernels

Luc De Raedt, Paolo Frasconi, Francesco Orsini, 2015, IJCAI.

Stochastic Constraint Programming with And-Or Branch-and-Bound

Luc De Raedt, Tias Guns, Behrouz Babaki, 2017, IJCAI.

Neuro-Symbolic = Neural + Logical + Probabilistic

Luc De Raedt, Sebastijan Dumancic, Angelika Kimmig, 2019, NeSy@IJCAI.

Mapping probability word problems to executable representations

Luc De Raedt, Walter Daelemans, Simon Suster, 2021, EMNLP.

Shape Inference and Grammar Induction for Example-based Procedural Generation

Luc De Raedt, Thomas Winters, Gillis Hermans, 2021, ICCC.

Automating Data Science: Prospects and Challenges pdf

Luc De Raedt, Tijl De Bie, Padhraic Smyth, 2021, ArXiv.

A Table-Based Representation for Probabilistic Logic: Preliminary Results pdf

Luc De Raedt, Joost Vennekens, Simon Vandevelde, 2021, ArXiv.

Muppets: Multipurpose Table Segmentation

Luc De Raedt, José Hernández-Orallo, Lidia Contreras Ochando, 2021, IDA.

avatar - Automated Feature Wrangling for Machine Learning

Luc De Raedt, Elia Van Wolputte, Gust Verbruggen, 2021, IDA.

SMProbLog: Stable Model Semantics in ProbLog and its Applications in Argumentation pdf

Luc De Raedt, Angelika Kimmig, Pietro Totis, 2021, ArXiv.

First-Order Context-Specific Likelihood Weighting in Hybrid Probabilistic Logic Programs

Luc De Raedt, Ondrej Kuzelka, Nitesh Kumar, 2022 .

Learning Mixed-Integer Linear Programs from Contextual Examples pdf

Luc De Raedt, Samuel Kolb, Stefano Teso, 2021, ArXiv.

SpLyCI: Integrating Spreadsheets by Recognising and Solving Layout Constraints

Luc De Raedt, Dirko Coetsee, McElory Hoffmann, 2021, IDA.

DeepStochLog: Neural Stochastic Logic Programming pdf

Luc De Raedt, Robin Manhaeve, Thomas Winters, 2021, AAAI.

Learning CNF Theories Using MDL and Predicate Invention

Luc De Raedt, Angelika Kimmig, Clément Gautrais, 2021, IJCAI.

Learning Distributional Programs for Relational Autocompletion pdf

Nitesh Kumar, Luc De Raedt, Ondrej Kuzelka, 2020, Theory Pract. Log. Program..

Approximate Inference for Neural Probabilistic Logic Programming

Luc De Raedt, Robin Manhaeve, Giuseppe Marra, 2021, KR.

Leaving Goals on the Pitch: Evaluating Decision Making in Soccer pdf

Luc De Raedt, Jesse Davis, Pieter Robberechts, 2021, ArXiv.

Approaches and Applications of Inductive Programming (Dagstuhl Seminar 21192)

Luc De Raedt, Andrew Cropper, Ute Schmid, 2021, Dagstuhl Reports.

From Statistical Relational to Neural Symbolic Artificial Intelligence: a Survey pdf

Luc De Raedt, Robin Manhaeve, Sebastijan Dumancic, 2021, ArXiv.

Democratizing Constraint Satisfaction Problems through Machine Learning

Luc De Raedt, Samuel Kolb, Clément Gautrais, 2021, AAAI.

Lifted model checking for relational MDPs pdf

Luc De Raedt, Wen-Chi Yang, Jean-Franccois Raskin, 2021, Machine Learning.

Data Mining and Machine Learning Techniques for the Identification of Mutagenicity Inducing Substructures and Structure—Activity Relationships of Noncongeneric Compounds.

Luc De Raedt, Christoph Helma, Stefan Kramer, 2004 .

SMIREP: Predicting Chemical Activity from SMILES.

Luc De Raedt, Andreas Karwath, L. D. Raedt, 2007 .

Probabilistic logic in dynamic domains: Particle filter with distributional clauses

Luc De Raedt, Guy Van den Broeck, Davide Nitti, 2011 .

Learning from Satissability

Luc De Raedt, L. D. Raedt, 1997 .

From non-deterministic to probabilistic planning with the help of statistical relational learning

Luc De Raedt, Bernd Gutmann, Ingo Thon, 2009 .

An interactive learning approach to histology image segmentation

Luc De Raedt, Laura Antanas, Fabian Guiza Grandas, 2012 .

Maximum common subgraph mining: A fast and effective approach towards feature generation

Luc De Raedt, Jan Ramon, Fabrizio Costa, 2009, MLG 2009.

Special issue on inductive logic programming

Luc De Raedt, Stefan Wrobel, L. D. Raedt, 2001 .

Discovering quantitative laws in inductive logic programming

Luc De Raedt, Wim Van Laer, L. D. Raedt, 1993 .

Learning to survive

Luc De Raedt, Maurice Bruynooghe, Bart Swennen, 1993 .