De Raedt, Luc

107 publications

ICLRW 2025 Can Large Language Models Reason? a Characterization via 3-SAT Rishi Hazra, Gabriele Venturato, Pedro Zuidberg Dos Martires, Luc De Raedt

NeurIPS 2025 LexiCon: A Benchmark for Planning Under Temporal Constraints in Natural Language Periklis Mantenoglou, Rishi Hazra, Pedro Zuidberg Dos Martires, Luc De Raedt

IJCAI 2025 NeSyA: Neurosymbolic Automata Nikolaos Manginas, George Paliouras, Luc De Raedt

AAAI 2025 Neurosymbolic Reinforcement Learning: Playing MiniHack with Probabilistic Logic Shields David Debot, Gabriele Venturato, Giuseppe Marra, Luc De Raedt

ECML-PKDD 2025 Queryable and Interpretable PU Learning Through Probabilistic Circuits Sieben Bocklandt, Vincent Derkinderen, Koen Vanderstraeten, Wouter Pijpops, Kurt Jaspers, Luc De Raedt, Wannes Meert

AAAI 2025 Relational Neurosymbolic Markov Models Lennert De Smet, Gabriele Venturato, Luc De Raedt, Giuseppe Marra

AAAI 2025 The Gradient of Algebraic Model Counting Jaron Maene, Luc De Raedt

AAAI 2024 Inference and Learning in Dynamic Decision Networks Using Knowledge Compilation Gabriele Venturato, Vincent Derkinderen, Pedro Zuidberg Dos Martires, Luc De Raedt

MLJ 2024 Modeling PU Learning Using Probabilistic Logic Programming Victor Verreet, Luc De Raedt, Jessa Bekker

ICMLW 2024 Neurosymbolic Markov Models Lennert De Smet, Gabriele Venturato, Luc De Raedt, Giuseppe Marra

ICML 2024 On the Hardness of Probabilistic Neurosymbolic Learning Jaron Maene, Vincent Derkinderen, Luc De Raedt

AAAI 2024 SayCanPay: Heuristic Planning with Large Language Models Using Learnable Domain Knowledge Rishi Hazra, Pedro Zuidberg Dos Martires, Luc De Raedt

JAIR 2023 A Markov Framework for Learning and Reasoning About Strategies in Professional Soccer Maaike Van Roy, Pieter Robberechts, Wen-Chi Yang, Luc De Raedt, Jesse Davis

ECML-PKDD 2023 Deep Explainable Relational Reinforcement Learning: A Neuro-Symbolic Approach Rishi Hazra, Luc De Raedt

JAIR 2023 First-Order Context-Specific Likelihood Weighting in Hybrid Probabilistic Logic Programs Nitesh Kumar, Ondrej Kuzelka, Luc De Raedt

JAIR 2023 Lifted Reasoning for Combinatorial Counting Pietro Totis, Jesse Davis, Luc De Raedt, Angelika Kimmig

UAI 2023 Neural Probabilistic Logic Programming in Discrete-Continuous Domains Lennert De Smet, Pedro Zuidberg Dos Martires, Robin Manhaeve, Giuseppe Marra, Angelika Kimmig, Luc De Raedt

IJCAI 2023 Safe Reinforcement Learning via Probabilistic Logic Shields Wen-Chi Yang, Giuseppe Marra, Gavin Rens, Luc De Raedt

NeurIPS 2023 Soft-Unification in Deep Probabilistic Logic Jaron Maene, Luc De Raedt

AAAI 2022 DeepStochLog: Neural Stochastic Logic Programming Thomas Winters, Giuseppe Marra, Robin Manhaeve, Luc De Raedt

AAAI 2022 Inference and Learning with Model Uncertainty in Probabilistic Logic Programs Victor Verreet, Vincent Derkinderen, Pedro Zuidberg Dos Martires, Luc De Raedt

MLJ 2022 Lifted Model Checking for Relational MDPs Wen-Chi Yang, Jean-François Raskin, Luc De Raedt

AAAI 2021 Democratizing Constraint Satisfaction Problems Through Machine Learning Mohit Kumar, Samuel Kolb, Clément Gautrais, Luc De Raedt

IJCAI 2021 Learning CNF Theories Using MDL and Predicate Invention Arcchit Jain, Clément Gautrais, Angelika Kimmig, Luc De Raedt

IJCAI 2020 From Statistical Relational to Neuro-Symbolic Artificial Intelligence Luc De Raedt, Sebastijan Dumancic, Robin Manhaeve, Giuseppe Marra

AAAI 2020 Learning MAX-SAT from Contextual Examples for Combinatorial Optimisation Mohit Kumar, Samuel Kolb, Stefano Teso, Luc De Raedt

MLJ 2020 Predictive Spreadsheet Autocompletion with Constraints Samuel Kolb, Stefano Teso, Anton Dries, Luc De Raedt

IJCAI 2020 ProbAnch: A Modular Probabilistic Anchoring Framework Andreas Persson, Pedro Zuidberg Dos Martires, Luc De Raedt, Amy Loutfi

ECML-PKDD 2020 VisualSynth: Democratizing Data Science in Spreadsheets Clément Gautrais, Yann Dauxais, Samuel Kolb, Arcchit Jain, Mohit Kumar, Stefano Teso, Elia Van Wolputte, Gust Verbruggen, Luc De Raedt

IJCAI 2019 Acquiring Integer Programs from Data Mohit Kumar, Stefano Teso, Luc De Raedt

AAAI 2019 Exact and Approximate Weighted Model Integration with Probability Density Functions Using Knowledge Compilation Pedro Zuidberg Dos Martires, Anton Dries, Luc De Raedt

UAI 2019 How to Exploit Structure While Solving Weighted Model Integration Problems Samuel Kolb, Pedro Zuidberg Dos Martires, Luc De Raedt

IJCAI 2019 The Pywmi Framework and Toolbox for Probabilistic Inference Using Weighted Model Integration Samuel Kolb, Paolo Morettin, Pedro Zuidberg Dos Martires, Francesco Sommavilla, Andrea Passerini, Roberto Sebastiani, Luc De Raedt

NeurIPSW 2019 Transforming Probabilistic Programs into Algebraic Circuits for Inference and Learning Pedro Zuidberg Dos Martires, Vincent Derkinderen, Robin Manhaeve, Wannes Meert, Angelika Kimmig, Luc De Raedt

NeurIPS 2018 DeepProbLog: Neural Probabilistic Logic Programming Robin Manhaeve, Sebastijan Dumancic, Angelika Kimmig, Thomas Demeester, Luc De Raedt

AAAI 2018 Learning Constraints from Examples Luc De Raedt, Andrea Passerini, Stefano Teso

IJCAI 2018 Learning SMT(LRA) Constraints Using SMT Solvers Samuel Kolb, Stefano Teso, Andrea Passerini, Luc De Raedt

MLJ 2017 Learning Constraints in Spreadsheets and Tabular Data Samuel Kolb, Sergey Paramonov, Tias Guns, Luc De Raedt

MLJ 2017 Planning in Hybrid Relational MDPs Davide Nitti, Vaishak Belle, Tinne De Laet, Luc De Raedt

MLJ 2017 Relational Data Factorization Sergey Paramonov, Matthijs van Leeuwen, Luc De Raedt

IJCAI 2017 Solving Probability Problems in Natural Language Anton Dries, Angelika Kimmig, Jesse Davis, Vaishak Belle, Luc De Raedt

IJCAI 2017 Stochastic Constraint Programming with And-or Branch-and-Bound Behrouz Babaki, Tias Guns, Luc De Raedt

MLJ 2017 kProbLog: An Algebraic Prolog for Machine Learning Francesco Orsini, Paolo Frasconi, Luc De Raedt

MLJ 2016 Probabilistic Logic Programming for Hybrid Relational Domains Davide Nitti, Tinne De Laet, Luc De Raedt

IJCAI 2015 Anytime Inference in Probabilistic Logic Programs with Tp-Compilation Jonas Vlasselaer, Guy Van den Broeck, Angelika Kimmig, Wannes Meert, Luc De Raedt

IJCAI 2015 Graph Invariant Kernels Francesco Orsini, Paolo Frasconi, Luc De Raedt

IJCAI 2015 Inducing Probabilistic Relational Rules from Probabilistic Examples Luc De Raedt, Anton Dries, Ingo Thon, Guy Van den Broeck, Mathias Verbeke

AAAI 2015 Languages for Learning and Mining Luc De Raedt

ECML-PKDD 2015 Planning in Discrete and Continuous Markov Decision Processes by Probabilistic Programming Davide Nitti, Vaishak Belle, Luc De Raedt

ECML-PKDD 2015 ProbLog2: Probabilistic Logic Programming Anton Dries, Angelika Kimmig, Wannes Meert, Joris Renkens, Guy Van den Broeck, Jonas Vlasselaer, Luc De Raedt

MLJ 2015 Probabilistic (logic) Programming Concepts Luc De Raedt, Angelika Kimmig

IJCAI 2015 kLog: A Language for Logical and Relational Learning with Kernels (Extended Abstract) Paolo Frasconi, Fabrizio Costa, Luc De Raedt, Kurt De Grave

ECML-PKDD 2014 Distributional Clauses Particle Filter Davide Nitti, Tinne De Laet, Luc De Raedt

AAAI 2014 Explanation-Based Approximate Weighted Model Counting for Probabilistic Logics Joris Renkens, Angelika Kimmig, Guy Van den Broeck, Luc De Raedt

ECML-PKDD 2014 Ranked Tiling Thanh Le Van, Matthijs van Leeuwen, Siegfried Nijssen, Ana Carolina Fierro, Kathleen Marchal, Luc De Raedt

WACV 2014 Towards Cautious Collective Inference for Object Verification José Oramas M., Luc De Raedt, Tinne Tuytelaars

WACV 2013 A Relational Kernel-Based Approach to Scene Classification Laura Antanas, McElory Hoffmann, Paolo Frasconi, Tinne Tuytelaars, Luc De Raedt

ICCV 2013 Allocentric Pose Estimation M. Jose Antonio, Luc De Raedt, Tinne Tuytelaars

IJCAI 2013 MiningZinc: A Modeling Language for Constraint-Based Mining Tias Guns, Anton Dries, Guido Tack, Siegfried Nijssen, Luc De Raedt

ALT 2012 Declarative Modeling for Machine Learning and Data Mining Luc De Raedt

ECML-PKDD 2012 Declarative Modeling for Machine Learning and Data Mining Luc De Raedt

MLJ 2012 ILP Turns 20 - Biography and Future Challenges Stephen H. Muggleton, Luc De Raedt, David Poole, Ivan Bratko, Peter A. Flach, Katsumi Inoue, Ashwin Srinivasan

AAAI 2011 An Algebraic Prolog for Reasoning About Possible Worlds Angelika Kimmig, Guy Van den Broeck, Luc De Raedt

MLJ 2011 Effective Feature Construction by Maximum Common Subgraph Sampling Leander Schietgat, Fabrizio Costa, Jan Ramon, Luc De Raedt

MLJ 2011 Guest Editorial to the Special Issue on Inductive Logic Programming, Mining and Learning in Graphs and Statistical Relational Learning Hendrik Blockeel, Karsten M. Borgwardt, Luc De Raedt, Pedro M. Domingos, Kristian Kersting, Xifeng Yan

UAI 2011 Inference in Probabilistic Logic Programs Using Weighted CNF's Daan Fierens, Guy Van den Broeck, Ingo Thon, Bernd Gutmann, Luc De Raedt

ECML-PKDD 2011 Learning the Parameters of Probabilistic Logic Programs from Interpretations Bernd Gutmann, Ingo Thon, Luc De Raedt

IJCAI 2011 Lifted Probabilistic Inference by First-Order Knowledge Compilation Guy Van den Broeck, Nima Taghipour, Wannes Meert, Jesse Davis, Luc De Raedt

MLJ 2011 Stochastic Relational Processes: Efficient Inference and Applications Ingo Thon, Niels Landwehr, Luc De Raedt

AAAI 2010 Constraint Programming for Data Mining and Machine Learning Luc De Raedt, Tias Guns, Siegfried Nijssen

AAAI 2010 DTProbLog: A Decision-Theoretic Probabilistic Prolog Guy Van den Broeck, Ingo Thon, Martijn van Otterlo, Luc De Raedt

MLJ 2010 Fast Learning of Relational Kernels Niels Landwehr, Andrea Passerini, Luc De Raedt, Paolo Frasconi

MLJ 2009 Cluster-Grouping: From Subgroup Discovery to Clustering Albrecht Zimmermann, Luc De Raedt

IJCAI 2009 Local Query Mining in a Probabilistic Prolog Angelika Kimmig, Luc De Raedt

ECML-PKDD 2008 A Simple Model for Sequences of Relational State Descriptions Ingo Thon, Niels Landwehr, Luc De Raedt

MLJ 2008 Compressing Probabilistic Prolog Programs Luc De Raedt, Kristian Kersting, Angelika Kimmig, Kate Revoredo, Hannu Toivonen

ECML-PKDD 2008 Parameter Learning in Probabilistic Databases: A Least Squares Approach Bernd Gutmann, Angelika Kimmig, Kristian Kersting, Luc De Raedt

JMLR 2007 Integrating Naïve Bayes and FOIL Niels Landwehr, Kristian Kersting, Luc De Raedt

IJCAI 2007 On Mining Closed Sets in Multi-Relational Data Gemma C. Garriga, Roni Khardon, Luc De Raedt

IJCAI 2007 ProbLog: A Probabilistic Prolog and Its Application in Link Discovery Luc De Raedt, Angelika Kimmig, Hannu Toivonen

IJCAI 2007 R-Grams: Relational Grams Niels Landwehr, Luc De Raedt

JMLR 2006 Kernels on Prolog Proof Trees: Statistical Learning in the ILP Setting Andrea Passerini, Paolo Frasconi, Luc De Raedt

JAIR 2006 Logical Hidden Markov Models Kristian Kersting, Luc De Raedt, Tapani Raiko

AAAI 2006 kFOIL: Learning Simple Relational Kernels Niels Landwehr, Andrea Passerini, Luc De Raedt, Paolo Frasconi

AAAI 2005 Towards Learning Stochastic Logic Programs from Proof-Banks Luc De Raedt, Kristian Kersting, Sunna Torge

AAAI 2005 nFOIL: Integrating Naïve Bayes and FOIL Niels Landwehr, Kristian Kersting, Luc De Raedt

ICML 2004 Bellman Goes Relational Kristian Kersting, Martijn van Otterlo, Luc De Raedt

ECML-PKDD 2004 Cluster-Grouping: From Subgroup Discovery to Clustering Albrecht Zimmermann, Luc De Raedt

ALT 2004 Probabilistic Inductive Logic Programming Luc De Raedt, Kristian Kersting

ECML-PKDD 2002 Phase Transitions and Stochastic Local Search in K-Term DNF Learning Ulrich Rückert, Stefan Kramer, Luc De Raedt

ICML 2001 Feature Construction with Version Spaces for Biochemical Applications Stefan Kramer, Luc De Raedt

MLJ 2001 Relational Reinforcement Learning Saso Dzeroski, Luc De Raedt, Kurt Driessens

IJCAI 2001 The Levelwise Version Space Algorithm and Its Application to Molecular Fragment Finding Luc De Raedt, Stefan Kramer

ICML 1998 Relational Reinforcement Learning Saso Dzeroski, Luc De Raedt, Hendrik Blockeel

ICML 1998 Top-Down Induction of Clustering Trees Hendrik Blockeel, Luc De Raedt, Jan Ramon

MLJ 1997 Clausal Discovery Luc De Raedt, Luc Dehaspe

ECML-PKDD 1997 Theta-Subsumption for Structural Matching Luc De Raedt, Peter Idestam-Almquist, Gunther Sablon

MLJ 1995 Declarative Bias for Specific-to-General ILP Systems Hilde Adé, Luc De Raedt, Maurice Bruynooghe

IJCAI 1995 Forgetting and Compacting Data in Concept Learning Gunther Sablon, Luc De Raedt

ALT 1995 Inductive Constraint Logic Luc De Raedt, Wim Van Laer

IJCAI 1993 A Theory of Clausal Discovery Luc De Raedt, Maurice Bruynooghe

IJCAI 1993 Multiple Predicate Learning Luc De Raedt, Nada Lavrac, Saso Dzeroski

MLJ 1992 Interactive Concept-Learning and Constructive Induction by Analogy Luc De Raedt, Maurice Bruynooghe

ICML 1991 Integrity Constraints and Interactive Concept-Learning Luc De Raedt, Maurice Bruynooghe, Bern Martens

ICML 1989 Constructive Induction by Analogy Luc De Raedt, Maurice Bruynooghe

IJCAI 1989 Explanation Based Program Transformation Maurice Bruynooghe, Luc De Raedt, Danny De Schreye

IJCAI 1989 Towards Friendly Concept-Learners Luc De Raedt, Maurice Bruynooghe