Luc De Raedt - RankMe

454 papers A* 67A 25B 50C 16Misc 2Journal 170Unranked 86

Year	Rank	Type	Title / Venue / Authors
2026	A*	`conf`	DeepProofLog: Efficient Proving in Deep Stochastic Logic Programs. AAAI Ying Jiao, Rodrigo Castellano Ontiveros, Luc De Raedt, Marco Gori, Francesco Giannini, Michelangelo Diligenti, Giuseppe Marra
2026	J	`jnl`	Tadmo: A tabular distance measure with move operations. Pattern Recognit. Lett. Dirko Coetsee, Steve Kroon, Ralf Kistner, Adem Kikaj, McElory Hoffmann, Luc De Raedt
2025	—	`conf`	A Learning and Reasoning Manifesto. Challenges and Algorithms for Knowledge Discovery from Data Luc De Raedt, Fredrik Heintz, Kristian Kersting, Giuseppe Marra
2025	J	`jnl`	Correction to: Modeling PU learning using probabilistic logic programming. Mach. Learn. Victor Verreet, Luc De Raedt, Jessa Bekker
2025	A	`conf`	DEEPGRAPHLOG for Layered Neurosymbolic AI. ECAI Adem Kikaj, Giuseppe Marra, Floris Geerts, Robin Manhaeve, Luc De Raedt
2025	J	`jnl`	DeepGraphLog for Layered Neurosymbolic AI. CoRR Adem Kikaj, Giuseppe Marra, Floris Geerts, Robin Manhaeve, Luc De Raedt
2025	J	`jnl`	DeepProofLog: Efficient Proving in Deep Stochastic Logic Programs. CoRR Ying Jiao, Rodrigo Castellano Ontiveros, Luc De Raedt, Marco Gori, Francesco Giannini, Michelangelo Diligenti, Giuseppe Marra
2025	J	`jnl`	Defining neurosymbolic AI. CoRR Lennert De Smet, Luc De Raedt
2025	J	`jnl`	Have Large Language Models Learned to Reason? A Characterization via 3-SAT Phase Transition. CoRR Rishi Hazra, Gabriele Venturato, Pedro Zuidberg Dos Martires, Luc De Raedt
2025	J	`jnl`	LexiCon: a Benchmark for Planning under Temporal Constraints in Natural Language. CoRR Periklis Mantenoglou, Rishi Hazra, Pedro Zuidberg Dos Martires, Luc De Raedt
2025	A*	`conf`	NeSyA: Neurosymbolic Automata. IJCAI Nikolaos Manginas, George Paliouras, Luc De Raedt
2025	J	`jnl`	Neurosymbolic Decision Trees. CoRR Matthias Möller, Arvid Norlander, Pedro Zuidberg Dos Martires, Luc De Raedt
2025	A	`conf`	Neurosymbolic OCR for Handwritten Tax Forms. ECAI Quinten Dewulf, Robin Manhaeve, Wannes Meert, Luc De Raedt
2025	A*	`conf`	Neurosymbolic Reinforcement Learning: Playing MiniHack with Probabilistic Logic Shields. AAAI David Debot, Gabriele Venturato, Giuseppe Marra, Luc De Raedt
2025	—	`conf`	Queryable and Interpretable PU Learning Through Probabilistic Circuits. ECML/PKDD (3) Sieben Bocklandt, Vincent Derkinderen, Koen Vanderstraeten, Wouter Pijpops, Kurt Jaspers, Luc De Raedt, Wannes Meert
2025	A*	`conf`	Relational Neurosymbolic Markov Models. AAAI Lennert De Smet, Gabriele Venturato, Luc De Raedt, Giuseppe Marra
2025	A	`conf`	TABIA: A Language to Transform, Combine, and Reason over Semi-Structured Tabular Data. ECAI Dirko Coetsee, Steve Kroon, McElory Hoffmann, Luc De Raedt
2025	J	`jnl`	The DeepLog Neurosymbolic Machine. CoRR Vincent Derkinderen, Robin Manhaeve, Rik Adriaensen, Lucas Van Praet, Lennert De Smet, Giuseppe Marra, Luc De Raedt
2025	A*	`conf`	The Gradient of Algebraic Model Counting. AAAI Jaron Maene, Luc De Raedt
2025	J	`jnl`	The Gradient of Algebraic Model Counting. CoRR Jaron Maene, Luc De Raedt
2025	J	`jnl`	Valid Text-to-SQL Generation with Unification-based DeepStochLog. CoRR Ying Jiao, Luc De Raedt, Giuseppe Marra
2024	—	`conf`	Approximate Compression of CNF Concepts. DS (2) Sieben Bocklandt, Vincent Derkinderen, Angelika Kimmig, Luc De Raedt
2024	A*	`conf`	Automated Reasoning in Systems Biology: A Necessity for Precision Medicine. KR Pedro Zuidberg Dos Martires, Vincent Derkinderen, Luc De Raedt, Marcus Krantz
2024	J	`jnl`	Automated Reasoning in Systems Biology: a Necessity for Precision Medicine. CoRR Pedro Zuidberg Dos Martires, Vincent Derkinderen, Luc De Raedt, Marcus Krantz
2024	—	`conf`	Benchmarking in Neuro-Symbolic AI. IJCLR Robin Manhaeve, Francesco Giannini, Mehdi Ali, Damiano Azzolini, Alice Bizzarri, Andrea Borghesi, Samuele Bortolotti, Luc De Raedt, Devendra Singh Dhami, Michelangelo Diligenti, Sebastijan Dumancic, Boi Faltings, Elisabetta Gentili, Alfonso Gerevini, Marco Gori, Tias Guns, Martin Homola, Kristian Kersting, Jens Lehmann, Michele Lombardi, Luca Salvatore Lorello, Emanuele Marconato, Stefano Melacci, Andrea Passerini, Debjit Paul, Fabrizio Riguzzi, Stefano Teso, Neil Yorke-Smith, Marco Lippi
2024	—	`conf`	CLEVR-POC: Reasoning-Intensive Visual Question Answering in Partially Observable Environments. LREC/COLING Savitha Sam Abraham, Marjan Alirezaie, Luc De Raedt
2024	J	`jnl`	CLEVR-POC: Reasoning-Intensive Visual Question Answering in Partially Observable Environments. CoRR Savitha Sam Abraham, Marjan Alirezaie, Luc De Raedt
2024	J	`jnl`	Can Large Language Models Reason? A Characterization via 3-SAT. CoRR Rishi Hazra, Gabriele Venturato, Pedro Zuidberg Dos Martires, Luc De Raedt
2024	J	`jnl`	Declarative probabilistic logic programming in discrete-continuous domains. Artif. Intell. Pedro Zuidberg Dos Martires, Luc De Raedt, Angelika Kimmig
2024	A	`conf`	EXPLAIN, AGREE, LEARN: Scaling Learning for Neural Probabilistic Logic. ECAI Victor Verreet, Lennert De Smet, Luc De Raedt, Emanuele Sansone
2024	J	`jnl`	EXPLAIN, AGREE, LEARN: Scaling Learning for Neural Probabilistic Logic. CoRR Victor Verreet, Lennert De Smet, Luc De Raedt, Emanuele Sansone
2024	J	`jnl`	From statistical relational to neurosymbolic artificial intelligence: A survey. Artif. Intell. Giuseppe Marra, Sebastijan Dumancic, Robin Manhaeve, Luc De Raedt
2024	A*	`conf`	Inference and Learning in Dynamic Decision Networks Using Knowledge Compilation. AAAI Gabriele Venturato, Vincent Derkinderen, Pedro Zuidberg Dos Martires, Luc De Raedt
2024	J	`jnl`	Modeling PU learning using probabilistic logic programming. Mach. Learn. Victor Verreet, Luc De Raedt, Jessa Bekker
2024	J	`jnl`	NeSyA: Neurosymbolic Automata. CoRR Nikolaos Manginas, George Paliouras, Luc De Raedt
2024	A*	`conf`	On the Hardness of Probabilistic Neurosymbolic Learning. ICML Jaron Maene, Vincent Derkinderen, Luc De Raedt
2024	J	`jnl`	On the Hardness of Probabilistic Neurosymbolic Learning. CoRR Jaron Maene, Vincent Derkinderen, Luc De Raedt
2024	J	`jnl`	Relational Neurosymbolic Markov Models. CoRR Lennert De Smet, Gabriele Venturato, Luc De Raedt, Giuseppe Marra
2024	A*	`conf`	SayCanPay: Heuristic Planning with Large Language Models Using Learnable Domain Knowledge. AAAI Rishi Hazra, Pedro Zuidberg Dos Martires, Luc De Raedt
2024	J	`jnl`	Semirings for Probabilistic and Neuro-Symbolic Logic Programming. CoRR Vincent Derkinderen, Robin Manhaeve, Pedro Zuidberg Dos Martires, Luc De Raedt
2024	J	`jnl`	Semirings for probabilistic and neuro-symbolic logic programming. Int. J. Approx. Reason. Vincent Derkinderen, Robin Manhaeve, Pedro Zuidberg Dos Martires, Luc De Raedt
2024	—	`conf`	Subgraph Mining for Graph Neural Networks. IDA (1) Adem Kikaj, Giuseppe Marra, Luc De Raedt
2024	—	`conf`	Valid Text-to-SQL Generation with Unification-Based DeepStochLog. NeSy (1) Ying Jiao, Luc De Raedt, Giuseppe Marra
2023	J	`jnl`	A Markov Framework for Learning and Reasoning About Strategies in Professional Soccer. J. Artif. Intell. Res. Maaike Van Roy, Pieter Robberechts, Wen-Chi Yang, Luc De Raedt, Jesse Davis
2023	J	`jnl`	Approaches and Applications of Inductive Programming (Dagstuhl Seminar 23442). Dagstuhl Reports Luc De Raedt, Ute Schmid, Johannes Langer
2023	J	`jnl`	Declarative Probabilistic Logic Programming in Discrete-Continuous Domains. CoRR Pedro Zuidberg Dos Martires, Luc De Raedt, Angelika Kimmig
2023	—	`conf`	Deep Explainable Relational Reinforcement Learning: A Neuro-Symbolic Approach. ECML/PKDD (4) Rishi Hazra, Luc De Raedt
2023	J	`jnl`	Deep Explainable Relational Reinforcement Learning: A Neuro-Symbolic Approach. CoRR Rishi Hazra, Luc De Raedt
2023	J	`jnl`	First-Order Context-Specific Likelihood Weighting in Hybrid Probabilistic Logic Programs. J. Artif. Intell. Res. Nitesh Kumar, Ondrej Kuzelka, Luc De Raedt
2023	J	`jnl`	Learning MAX-SAT from contextual examples for combinatorial optimisation. Artif. Intell. Mohit Kumar, Samuel Kolb, Stefano Teso, Luc De Raedt
2023	J	`jnl`	Lifted Reasoning for Combinatorial Counting. J. Artif. Intell. Res. Pietro Totis, Jesse Davis, Luc De Raedt, Angelika Kimmig
2023	J	`jnl`	Neural Probabilistic Logic Programming in Discrete-Continuous Domains. CoRR Lennert De Smet, Pedro Zuidberg Dos Martires, Robin Manhaeve, Giuseppe Marra, Angelika Kimmig, Luc De Raedt
2023	A	`conf`	Neural probabilistic logic programming in discrete-continuous domains. UAI Lennert De Smet, Pedro Zuidberg Dos Martires, Robin Manhaeve, Giuseppe Marra, Angelika Kimmig, Luc De Raedt
2023	A*	`conf`	Safe Reinforcement Learning via Probabilistic Logic Shields. IJCAI Wen-Chi Yang, Giuseppe Marra, Gavin Rens, Luc De Raedt
2023	C	`conf`	Safe Reinforcement Learning via Probabilistic Logic Shields. NeSy Wen-Chi Yang, Giuseppe Marra, Gavin Rens, Luc De Raedt
2023	J	`jnl`	Safe Reinforcement Learning via Probabilistic Logic Shields. CoRR Wen-Chi Yang, Giuseppe Marra, Gavin Rens, Luc De Raedt
2023	J	`jnl`	SayCanPay: Heuristic Planning with Large Language Models using Learnable Domain Knowledge. CoRR Rishi Hazra, Pedro Zuidberg Dos Martires, Luc De Raedt
2023	A*	`conf`	Soft-Unification in Deep Probabilistic Logic. NeurIPS Jaron Maene, Luc De Raedt
2023	J	`jnl`	The Collection of Papers Celebrating the 20th Anniversary of TPLP, Part II. Theory Pract. Log. Program. Thomas Eiter, Michael J. Maher, Enrico Pontelli, Luc De Raedt, Miroslaw Truszczynski
2023	J	`jnl`	sm Theory Pract. Log. Program. Pietro Totis, Luc De Raedt, Angelika Kimmig
2023	J	`jnl`	smProbLog: Stable Model Semantics in ProbLog for Probabilistic Argumentation. CoRR Pietro Totis, Angelika Kimmig, Luc De Raedt
2022	J	`jnl`	Automating data science. Commun. ACM Tijl De Bie, Luc De Raedt, José Hernández-Orallo, Holger H. Hoos, Padhraic Smyth, Christopher K. I. Williams
2022	A*	`conf`	DeepStochLog: Neural Stochastic Logic Programming. AAAI Thomas Winters, Giuseppe Marra, Robin Manhaeve, Luc De Raedt
2022	J	`jnl`	First-Order Context-Specific Likelihood Weighting in Hybrid Probabilistic Logic Programs. CoRR Nitesh Kumar, Ondrej Kuzelka, Luc De Raedt
2022	—	`ch.`	Human-Machine Collaboration for Democratizing Data Science. Human-Like Machine Intelligence Clément Gautrais, Yann Dauxais, Stefano Teso, Samuel Kolb, Gust Verbruggen, Luc De Raedt
2022	A*	`conf`	Inference and Learning with Model Uncertainty in Probabilistic Logic Programs. AAAI Victor Verreet, Vincent Derkinderen, Pedro Zuidberg Dos Martires, Luc De Raedt
2022	J	`jnl`	Introduction to the Collection of Papers Celebrating the 20th Anniversary of TPLP. Theory Pract. Log. Program. Thomas Eiter, Michael J. Maher, Enrico Pontelli, Luc De Raedt, Miroslaw Truszczynski
2022	J	`jnl`	Learning Distributional Programs for Relational Autocompletion. Theory Pract. Log. Program. Nitesh Kumar, Ondrej Kuzelka, Luc De Raedt
2022	J	`jnl`	Learning MAX-SAT from Contextual Examples for Combinatorial Optimisation. CoRR Mohit Kumar, Samuel Kolb, Stefano Teso, Luc De Raedt
2022	J	`jnl`	Learning Probabilistic Temporal Safety Properties from Examples in Relational Domains. CoRR Gavin Rens, Wen-Chi Yang, Jean-François Raskin, Luc De Raedt
2022	J	`jnl`	Lifted model checking for relational MDPs. Mach. Learn. Wen-Chi Yang, Jean-François Raskin, Luc De Raedt
2022	J	`jnl`	OMEN: network-based driver gene identification using mutual exclusivity. Bioinform. Dries Van Daele, Bram Weytjens, Luc De Raedt, Kathleen Marchal
2022	B	`conf`	Parameter Learning in ProbLog with Annotated Disjunctions. IDA Wen-Chi Yang, Arcchit Jain, Luc De Raedt, Wannes Meert
2022	A*	`ed.`	Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, IJCAI 2022, Vienna, Austria, 23-29 July 2022. IJCAI Luc De Raedt
2021	J	`jnl`	A Table-Based Representation for Probabilistic Logic: Preliminary Results. CoRR Simon Vandevelde, Victor Verreet, Luc De Raedt, Joost Vennekens
2021	J	`jnl`	Approaches and Applications of Inductive Programming (Dagstuhl Seminar 21192). Dagstuhl Reports Andrew Cropper, Luc De Raedt, Richard Evans, Ute Schmid
2021	A*	`conf`	Approximate Inference for Neural Probabilistic Logic Programming. KR Robin Manhaeve, Giuseppe Marra, Luc De Raedt
2021	J	`jnl`	Automating Data Science: Prospects and Challenges. CoRR Tijl De Bie, Luc De Raedt, José Hernández-Orallo, Holger H. Hoos, Padhraic Smyth, Christopher K. I. Williams
2021	J	`jnl`	DeepStochLog: Neural Stochastic Logic Programming. CoRR Thomas Winters, Giuseppe Marra, Robin Manhaeve, Luc De Raedt
2021	A*	`conf`	Democratizing Constraint Satisfaction Problems through Machine Learning. AAAI Mohit Kumar, Samuel Kolb, Clément Gautrais, Luc De Raedt
2021	J	`jnl`	From Statistical Relational to Neural Symbolic Artificial Intelligence: a Survey. CoRR Giuseppe Marra, Sebastijan Dumancic, Robin Manhaeve, Luc De Raedt
2021	A*	`conf`	Learning CNF Theories Using MDL and Predicate Invention. IJCAI Arcchit Jain, Clément Gautrais, Angelika Kimmig, Luc De Raedt
2021	J	`jnl`	Learning Mixed-Integer Linear Programs from Contextual Examples. CoRR Mohit Kumar, Samuel Kolb, Luc De Raedt, Stefano Teso
2021	J	`jnl`	Leaving Goals on the Pitch: Evaluating Decision Making in Soccer. CoRR Maaike Van Roy, Pieter Robberechts, Wen-Chi Yang, Luc De Raedt, Jesse Davis
2021	J	`jnl`	Lifted Model Checking for Relational MDPs. CoRR Wen-Chi Yang, Jean-François Raskin, Luc De Raedt
2021	—	`conf`	Mapping probability word problems to executable representations. EMNLP (1) Simon Suster, Pieter Fivez, Pietro Totis, Angelika Kimmig, Jesse Davis, Luc De Raedt, Walter Daelemans
2021	B	`conf`	Muppets: Multipurpose Table Segmentation. IDA Gust Verbruggen, Lidia Contreras Ochando, Cèsar Ferri, José Hernández-Orallo, Luc De Raedt
2021	J	`jnl`	Neural probabilistic logic programming in DeepProbLog. Artif. Intell. Robin Manhaeve, Sebastijan Dumancic, Angelika Kimmig, Thomas Demeester, Luc De Raedt
2021	—	`ch.`	Neuro-Symbolic AI = Neural + Logical + Probabilistic AI. Neuro-Symbolic Artificial Intelligence Robin Manhaeve, Giuseppe Marra, Thomas Demeester, Sebastijan Dumancic, Angelika Kimmig, Luc De Raedt
2021	J	`jnl`	SMProbLog: Stable Model Semantics in ProbLog and its Applications in Argumentation. CoRR Pietro Totis, Angelika Kimmig, Luc De Raedt
2021	C	`conf`	Shape Inference and Grammar Induction for Example-Based Procedural Generation. ICCC Gillis Hermans, Thomas Winters, Luc De Raedt
2021	J	`jnl`	Shape Inference and Grammar Induction for Example-based Procedural Generation. CoRR Gillis Hermans, Thomas Winters, Luc De Raedt
2021	B	`conf`	SpLyCI: Integrating Spreadsheets by Recognising and Solving Layout Constraints. IDA Dirko Coetsee, Steve Kroon, McElory Hoffmann, Luc De Raedt
2021	B	`conf`	avatar - Automated Feature Wrangling for Machine Learning. IDA Gust Verbruggen, Elia Van Wolputte, Sebastijan Dumancic, Luc De Raedt
2020	A	`conf`	Algebraic Circuits for Decision Theoretic Inference and Learning. ECAI Vincent Derkinderen, Luc De Raedt
2020	C	`conf`	Discovering Textual Structures: Generative Grammar Induction using Template Trees. ICCC Thomas Winters, Luc De Raedt
2020	J	`jnl`	Discovering Textual Structures: Generative Grammar Induction using Template Trees. CoRR Thomas Winters, Luc De Raedt
2020	A*	`conf`	From Statistical Relational to Neuro-Symbolic Artificial Intelligence. IJCAI Luc De Raedt, Sebastijan Dumancic, Robin Manhaeve, Giuseppe Marra
2020	J	`jnl`	From Statistical Relational to Neuro-Symbolic Artificial Intelligence. CoRR Luc De Raedt, Sebastijan Dumancic, Robin Manhaeve, Giuseppe Marra
2020	J	`jnl`	Human-Machine Collaboration for Democratizing Data Science. CoRR Clément Gautrais, Yann Dauxais, Stefano Teso, Samuel Kolb, Gust Verbruggen, Luc De Raedt
2020	J	`jnl`	Learning Distributional Programs for Relational Autocompletion. CoRR Nitesh Kumar, Ondrej Kuzelka, Luc De Raedt
2020	A*	`conf`	Learning MAX-SAT from Contextual Examples for Combinatorial Optimisation. AAAI Mohit Kumar, Samuel Kolb, Stefano Teso, Luc De Raedt
2020	A	`conf`	Ordering Variables for Weighted Model Integration. UAI Vincent Derkinderen, Evert Heylen, Pedro Zuidberg Dos Martires, Samuel Kolb, Luc De Raedt
2020	J	`jnl`	Predictive spreadsheet autocompletion with constraints. Mach. Learn. Samuel Kolb, Stefano Teso, Anton Dries, Luc De Raedt
2020	A*	`conf`	ProbAnch: a Modular Probabilistic Anchoring Framework. IJCAI Andreas Persson, Pedro Zuidberg Dos Martires, Luc De Raedt, Amy Loutfi
2020	J	`jnl`	Semantic Relational Object Tracking. IEEE Trans. Cogn. Dev. Syst. Andreas Persson, Pedro Zuidberg Dos Martires, Luc De Raedt, Amy Loutfi
2020	J	`jnl`	Semiring programming: A semantic framework for generalized sum product problems. Int. J. Approx. Reason. Vaishak Belle, Luc De Raedt
2020	J	`jnl`	Symbolic Learning and Reasoning With Noisy Data for Probabilistic Anchoring. Frontiers Robotics AI Pedro Zuidberg Dos Martires, Nitesh Kumar, Andreas Persson, Amy Loutfi, Luc De Raedt
2020	J	`jnl`	Symbolic Learning and Reasoning with Noisy Data for Probabilistic Anchoring. CoRR Pedro Zuidberg Dos Martires, Nitesh Kumar, Andreas Persson, Amy Loutfi, Luc De Raedt
2020	—	`conf`	VisualSynth: Democratizing Data Science in Spreadsheets. ECML/PKDD (5) Clément Gautrais, Yann Dauxais, Samuel Kolb, Arcchit Jain, Mohit Kumar, Stefano Teso, Elia Van Wolputte, Gust Verbruggen, Luc De Raedt
2019	A*	`conf`	Acquiring Integer Programs from Data. IJCAI Mohit Kumar, Stefano Teso, Luc De Raedt
2019	J	`jnl`	Approaches and Applications of Inductive Programming (Dagstuhl Seminar 19202). Dagstuhl Reports Luc De Raedt, Richard Evans, Stephen H. Muggleton, Ute Schmid
2019	B	`conf`	Automating Personnel Rostering by Learning Constraints Using Tensors. ICTAI Mohit Kumar, Stefano Teso, Patrick De Causmaecker, Luc De Raedt
2019	—	`conf`	DeepProbLog: Neural Probabilistic Logic Programming. BNAIC/BENELEARN Robin Manhaeve, Sebastijan Dumancic, Angelika Kimmig, Thomas Demeester, Luc De Raedt
2019	J	`jnl`	DeepProbLog: Neural Probabilistic Logic Programming. CoRR Robin Manhaeve, Sebastijan Dumancic, Angelika Kimmig, Thomas Demeester, Luc De Raedt
2019	A*	`conf`	Exact and Approximate Weighted Model Integration with Probability Density Functions Using Knowledge Compilation. AAAI Pedro Zuidberg Dos Martires, Anton Dries, Luc De Raedt
2019	A	`conf`	How to Exploit Structure while Solving Weighted Model Integration Problems. UAI Samuel Kolb, Pedro Zuidberg Dos Martires, Luc De Raedt
2019	J	`jnl`	Learning from Implicit Information in Natural Language Instructions for Robotic Manipulations. CoRR Ozan Arkan Can, Pedro Zuidberg Dos Martires, Andreas Persson, Julian Gaal, Amy Loutfi, Luc De Raedt, Deniz Yuret, Alessandro Saffiotti
2019	—	`conf`	Neuro-Symbolic = Neural + Logical + Probabilistic. NeSy@IJCAI Luc De Raedt, Robin Manhaeve, Sebastijan Dumancic, Thomas Demeester, Angelika Kimmig
2019	—	`conf`	Scalable Rule Learning in Probabilistic Knowledge Bases. AKBC Arcchit Jain, Tal Friedman, Ondrej Kuzelka, Guy Van den Broeck, Luc De Raedt
2019	J	`jnl`	Semantic Relational Object Tracking. CoRR Andreas Persson, Pedro Zuidberg Dos Martires, Amy Loutfi, Luc De Raedt
2019	J	`jnl`	Semantic and geometric reasoning for robotic grasping: a probabilistic logic approach. Auton. Robots Laura Antanas, Plinio Moreno, Marion Neumann, Rui Pimentel de Figueiredo, Kristian Kersting, José Santos-Victor, Luc De Raedt
2019	—	`conf`	SynthLog: A Language for Synthesising Inductive Data Models (Extended Abstract). PKDD/ECML Workshops (1) Yann Dauxais, Clément Gautrais, Anton Dries, Arcchit Jain, Samuel Kolb, Mohit Kumar, Stefano Teso, Elia Van Wolputte, Gust Verbruggen, Luc De Raedt
2019	A*	`conf`	The pywmi Framework and Toolbox for Probabilistic Inference using Weighted Model Integration. IJCAI Samuel Kolb, Paolo Morettin, Pedro Zuidberg Dos Martires, Francesco Sommavilla, Andrea Passerini, Roberto Sebastiani, Luc De Raedt
2018	B	`conf`	Automatically Wrangling Spreadsheets into Machine Learning Data Formats. IDA Gust Verbruggen, Luc De Raedt
2018	J	`jnl`	Automating Data Science (Dagstuhl Seminar 18401). Dagstuhl Reports Tijl De Bie, Luc De Raedt, Holger H. Hoos, Padhraic Smyth
2018	J	`jnl`	Automating Personnel Rostering by Learning Constraints Using Tensors. CoRR Mohit Kumar, Stefano Teso, Luc De Raedt
2018	A*	`conf`	DeepProbLog: Neural Probabilistic Logic Programming. NeurIPS Robin Manhaeve, Sebastijan Dumancic, Angelika Kimmig, Thomas Demeester, Luc De Raedt
2018	J	`jnl`	DeepProbLog: Neural Probabilistic Logic Programming. CoRR Robin Manhaeve, Sebastijan Dumancic, Angelika Kimmig, Thomas Demeester, Luc De Raedt
2018	B	`conf`	Elements of an Automatic Data Scientist. IDA Luc De Raedt, Hendrik Blockeel, Samuel Kolb, Stefano Teso, Gust Verbruggen
2018	J	`jnl`	Knowledge Compilation with Continuous Random Variables and its Application in Hybrid Probabilistic Logic Programming. CoRR Pedro Zuidberg Dos Martires, Anton Dries, Luc De Raedt
2018	A*	`conf`	Learning Constraints From Examples. AAAI Luc De Raedt, Andrea Passerini, Stefano Teso
2018	A*	`conf`	Learning SMT(LRA) Constraints using SMT Solvers. IJCAI Samuel Kolb, Stefano Teso, Andrea Passerini, Luc De Raedt
2018	J	`jnl`	Relational affordances for multiple-object manipulation. Auton. Robots Bogdan Moldovan, Plinio Moreno, Davide Nitti, José Santos-Victor, Luc De Raedt
2018	B	`conf`	Sketched Answer Set Programming. ICTAI Sergey Paramonov, Christian Bessiere, Anton Dries, Luc De Raedt
2017	J	`jnl`	Algebraic model counting. J. Appl. Log. Angelika Kimmig, Guy Van den Broeck, Luc De Raedt
2017	J	`jnl`	Context-based Object Viewpoint Estimation: A 2D Relational Approach. CoRR José Oramas M., Luc De Raedt, Tinne Tuytelaars
2017	J	`jnl`	Context-based object viewpoint estimation: A 2D relational approach. Comput. Vis. Image Underst. José Oramas M., Luc De Raedt, Tinne Tuytelaars
2017	J	`jnl`	Editors' Introduction to the Special Issue on "Information and Communication Technology". Informatica (Slovenia) Luc De Raedt, Marc Bui, Yves Deville, T. Dieu Linh Truong
2017	J	`jnl`	Flexible constrained sampling with guarantees for pattern mining. Data Min. Knowl. Discov. Vladimir Dzyuba, Matthijs van Leeuwen, Luc De Raedt
2017	—	`ch.`	Inductive Logic Programming. Encyclopedia of Machine Learning and Data Mining Luc De Raedt
2017	J	`jnl`	Learning constraints in spreadsheets and tabular data. Mach. Learn. Samuel Kolb, Sergey Paramonov, Tias Guns, Luc De Raedt
2017	—	`ch.`	Logic of Generality. Encyclopedia of Machine Learning and Data Mining Luc De Raedt
2017	J	`jnl`	MiningZinc: A declarative framework for constraint-based mining. Artif. Intell. Tias Guns, Anton Dries, Siegfried Nijssen, Guido Tack, Luc De Raedt
2017	—	`ch.`	Multi-relational Data Mining. Encyclopedia of Machine Learning and Data Mining Luc De Raedt
2017	J	`jnl`	Planning in hybrid relational MDPs. Mach. Learn. Davide Nitti, Vaishak Belle, Tinne De Laet, Luc De Raedt
2017	B	`conf`	Relational Affordance Learning for Task-Dependent Robot Grasping. ILP Laura Antanas, Anton Dries, Plinio Moreno, Luc De Raedt
2017	J	`jnl`	Relational data factorization. Mach. Learn. Sergey Paramonov, Matthijs van Leeuwen, Luc De Raedt
2017	J	`jnl`	Semiring Rank Matrix Factorization. IEEE Trans. Knowl. Data Eng. Thanh Le Van, Siegfried Nijssen, Matthijs van Leeuwen, Luc De Raedt
2017	J	`jnl`	Sketched Answer Set Programming. CoRR Sergey Paramonov, Christian Bessiere, Anton Dries, Luc De Raedt
2017	A*	`conf`	Solving Probability Problems in Natural Language. IJCAI Anton Dries, Angelika Kimmig, Jesse Davis, Vaishak Belle, Luc De Raedt
2017	—	`ch.`	Statistical Relational Learning. Encyclopedia of Machine Learning and Data Mining Luc De Raedt, Kristian Kersting
2017	A*	`conf`	Stochastic Constraint Programming with And-Or Branch-and-Bound. IJCAI Behrouz Babaki, Tias Guns, Luc De Raedt
2017	A	`conf`	TaCLe: Learning Constraints in Tabular Data. CIKM Sergey Paramonov, Samuel Kolb, Tias Guns, Luc De Raedt
2017	J	`jnl`	The Inductive Constraint Programming Loop. IEEE Intell. Syst. Christian Bessiere, Luc De Raedt, Tias Guns, Lars Kotthoff, Mirco Nanni, Siegfried Nijssen, Barry O'Sullivan, Anastasia Paparrizou, Dino Pedreschi, Helmut Simonis
2017	—	`conf`	Towards Automated Relational Data Wrangling. AutoML@PKDD/ECML Gust Verbruggen, Luc De Raedt
2017	J	`jnl`	kProbLog: an algebraic Prolog for machine learning. Mach. Learn. Francesco Orsini, Paolo Frasconi, Luc De Raedt
2016	—	`book`	Data Mining and Constraint Programming - Foundations of a Cross-Disciplinary Approach Data Mining and Constraint Programming Christian Bessiere, Luc De Raedt, Lars Kotthoff, Siegfried Nijssen, Barry O'Sullivan, Dino Pedreschi
2016	J	`jnl`	Exploiting local and repeated structure in Dynamic Bayesian Networks. Artif. Intell. Jonas Vlasselaer, Wannes Meert, Guy Van den Broeck, Luc De Raedt
2016	J	`jnl`	Flexible constrained sampling with guarantees for pattern mining. CoRR Vladimir Dzyuba, Matthijs van Leeuwen, Luc De Raedt
2016	J	`jnl`	Introduction to Special issue on "The Sixth International Symposium on Information and Communication Technology -SoICT 2015. Informatica (Slovenia) Luc De Raedt, Yves Deville, Marc Bui, Truong Thi Dieu Linh
2016	—	`conf`	Knowledge Compilation and Weighted Model Counting for Inference in Probabilistic Logic Programs. AAAI Workshop: Beyond NP Jonas Vlasselaer, Angelika Kimmig, Anton Dries, Wannes Meert, Luc De Raedt
2016	—	`ch.`	Learning Constraint Satisfaction Problems: An ILP Perspective. Data Mining and Constraint Programming Luc De Raedt, Anton Dries, Tias Guns, Christian Bessiere
2016	A	`conf`	Learning the Structure of Dynamic Hybrid Relational Models. ECAI Davide Nitti, Irma Ravkic, Jesse Davis, Luc De Raedt
2016	—	`ch.`	Modeling in MiningZinc. Data Mining and Constraint Programming Anton Dries, Tias Guns, Siegfried Nijssen, Behrouz Babaki, Thanh Le Van, Benjamin Négrevergne, Sergey Paramonov, Luc De Raedt
2016	J	`jnl`	Probabilistic logic programming for hybrid relational domains. Mach. Learn. Davide Nitti, Tinne De Laet, Luc De Raedt
2016	—	`conf`	Qualitative Spatial Reasoning for Soccer Pass Prediction. MLSA@PKDD/ECML Vincent Vercruyssen, Luc De Raedt, Jesse Davis
2016	J	`jnl`	Semiring Programming: A Framework for Search, Inference and Learning. CoRR Vaishak Belle, Luc De Raedt
2016	J	`jnl`	Simultaneous discovery of cancer subtypes and subtype features by molecular data integration. Bioinform. Thanh Le Van, Matthijs van Leeuwen, Ana Carolina Fierro, Dries De Maeyer, Jimmy Van den Eynden, Lieven P. C. Verbeke, Luc De Raedt, Kathleen Marchal, Siegfried Nijssen
2016	—	`book`	Statistical Relational Artificial Intelligence: Logic, Probability, and Computation Statistical Relational Artificial Intelligence Luc De Raedt, Kristian Kersting, Sriraam Natarajan, David Poole
2016	J	`jnl`	T Int. J. Approx. Reason. Jonas Vlasselaer, Guy Van den Broeck, Angelika Kimmig, Wannes Meert, Luc De Raedt
2016	—	`ch.`	The Inductive Constraint Programming Loop. Data Mining and Constraint Programming Christian Bessiere, Luc De Raedt, Tias Guns, Lars Kotthoff, Mirco Nanni, Siegfried Nijssen, Barry O'Sullivan, Anastasia Paparrizou, Dino Pedreschi, Helmut Simonis
2015	B	`conf`	An Exercise in Declarative Modeling for Relational Query Mining. ILP Sergey Paramonov, Matthijs van Leeuwen, Marc Denecker, Luc De Raedt
2015	A*	`conf`	Anytime Inference in Probabilistic Logic Programs with Tp-Compilation. IJCAI Jonas Vlasselaer, Guy Van den Broeck, Angelika Kimmig, Wannes Meert, Luc De Raedt
2015	B	`conf`	Constraint-Based Querying for Bayesian Network Exploration. IDA Behrouz Babaki, Tias Guns, Siegfried Nijssen, Luc De Raedt
2015	J	`jnl`	Exploring the efficacy of molecular fragments of different complexity in computational SAR modeling. CoRR Albrecht Zimmermann, Björn Bringmann, Luc De Raedt
2015	A*	`conf`	Graph Invariant Kernels. IJCAI Francesco Orsini, Paolo Frasconi, Luc De Raedt
2015	A*	`conf`	Inducing Probabilistic Relational Rules from Probabilistic Examples. IJCAI Luc De Raedt, Anton Dries, Ingo Thon, Guy Van den Broeck, Mathias Verbeke
2015	J	`jnl`	Inference and learning in probabilistic logic programs using weighted Boolean formulas. Theory Pract. Log. Program. Daan Fierens, Guy Van den Broeck, Joris Renkens, Dimitar Sht. Shterionov, Bernd Gutmann, Ingo Thon, Gerda Janssens, Luc De Raedt
2015	J	`jnl`	Introduction to the special issue on probability, logic and learning. Theory Pract. Log. Program. James Cussens, Luc De Raedt, Angelika Kimmig, Taisuke Sato
2015	A*	`conf`	Languages for Learning and Mining. AAAI Luc De Raedt
2015	J	`jnl`	Lazy Explanation-Based Approximation for Probabilistic Logic Programming. CoRR Joris Renkens, Angelika Kimmig, Luc De Raedt
2015	—	`conf`	Neural-Symbolic Learning and Reasoning: Contributions and Challenges. AAAI Spring Symposia Artur S. d'Avila Garcez, Tarek R. Besold, Luc De Raedt, Peter Földiák, Pascal Hitzler, Thomas Icard, Kai-Uwe Kühnberger, Luís C. Lamb, Risto Miikkulainen, Daniel L. Silver
2015	J	`jnl`	PheNetic: network-based interpretation of molecular profiling data. Nucleic Acids Res. Dries De Maeyer, Bram Weytjens, Joris Renkens, Luc De Raedt, Kathleen Marchal
2015	—	`conf`	Planning in Discrete and Continuous Markov Decision Processes by Probabilistic Programming. ECML/PKDD (2) Davide Nitti, Vaishak Belle, Luc De Raedt
2015	—	`conf`	ProbLog2: Probabilistic Logic Programming. ECML/PKDD (3) Anton Dries, Angelika Kimmig, Wannes Meert, Joris Renkens, Guy Van den Broeck, Jonas Vlasselaer, Luc De Raedt
2015	J	`jnl`	Probabilistic (logic) programming concepts. Mach. Learn. Luc De Raedt, Angelika Kimmig
2015	—	`ed.`	Proceedings of the Sixth International Symposium on Information and Communication Technology, Hue City, Vietnam, December 3-4, 2015 SoICT Huynh Quyet Thang, Le Anh Phuong, Luc De Raedt, Yves Deville, Marc Bui, Truong Thi Dieu Linh, Thi-Oanh Nguyen, Dinh Viet Sang, Nguyen Ba Ngoc
2015	—	`conf`	Rank Matrix Factorisation. PAKDD (1) Thanh Le Van, Matthijs van Leeuwen, Siegfried Nijssen, Luc De Raedt
2015	B	`conf`	Relational Kernel-Based Grasping with Numerical Features. ILP Laura Antanas, Plinio Moreno, Luc De Raedt
2015	J	`jnl`	The Inductive Constraint Programming Loop. CoRR Christian Bessiere, Luc De Raedt, Tias Guns, Lars Kotthoff, Mirco Nanni, Siegfried Nijssen, Barry O'Sullivan, Anastasia Paparrizou, Dino Pedreschi, Helmut Simonis
2015	A*	`conf`	kLog: A Language for Logical and Relational Learning with Kernels (Extended Abstract). IJCAI Paolo Frasconi, Fabrizio Costa, Luc De Raedt, Kurt De Grave
2015	B	`conf`	kProbLog: An Algebraic Prolog for Kernel Programming. ILP Francesco Orsini, Paolo Frasconi, Luc De Raedt
2014	—	`conf`	Application of Dynamic Distributional Clauses for Multi-hypothesis Initialization in Model-based Object Tracking. VISAPP (2) Davide Nitti, Georgios Chliveros, Maria Pateraki, Luc De Raedt, Emmanouil Hourdakis, Panos E. Trahanias
2014	A	`conf`	Condition Monitoring with Incomplete Observations. ECAI Jonas Vlasselaer, Wannes Meert, Rocco Langone, Luc De Raedt
2014	J	`jnl`	Constraints, Optimization and Data (Dagstuhl Seminar 14411). Dagstuhl Reports Luc De Raedt, Siegfried Nijssen, Barry O'Sullivan, Michèle Sebag
2014	—	`conf`	Distributional Clauses Particle Filter. ECML/PKDD (3) Davide Nitti, Tinne De Laet, Luc De Raedt
2014	—	`conf`	Efficient Probabilistic Inference for Dynamic Relational Models. StarAI@AAAI Jonas Vlasselaer, Wannes Meert, Guy Van den Broeck, Luc De Raedt
2014	A*	`conf`	Explanation-Based Approximate Weighted Model Counting for Probabilistic Logics. AAAI Joris Renkens, Angelika Kimmig, Guy Van den Broeck, Luc De Raedt
2014	—	`conf`	Explanation-Based Approximate Weighted Model Counting for Probabilistic Logics. StarAI@AAAI Joris Renkens, Angelika Kimmig, Guy Van den Broeck, Luc De Raedt
2014	J	`jnl`	High-level Reasoning and Low-level Learning for Grasping: A Probabilistic Logic Pipeline. CoRR Laura Antanas, Plinio Moreno, Marion Neumann, Rui Pimentel de Figueiredo, Kristian Kersting, José Santos-Victor, Luc De Raedt
2014	J	`jnl`	Interactive Learning of Pattern Rankings. Int. J. Artif. Intell. Tools Vladimir Dzyuba, Matthijs van Leeuwen, Siegfried Nijssen, Luc De Raedt
2014	J	`jnl`	Introduction to the Special Issue on the ECAI 2012 Turing and Anniversary Track. AI Commun. Maria Fox, Luc De Raedt
2014	—	`conf`	Lazy and Eager Relational Learning Using Graph-Kernels. SLSP Mathias Verbeke, Vincent Van Asch, Walter Daelemans, Luc De Raedt
2014	A	`conf`	Learning relational affordance models for two-arm robots. IROS Bogdan Moldovan, Luc De Raedt
2014	A*	`conf`	Occluded object search by relational affordances. ICRA Bogdan Moldovan, Luc De Raedt
2014	B	`conf`	PageRank, ProPPR, and Stochastic Logic Programs. ILP Dries Van Daele, Angelika Kimmig, Luc De Raedt
2014	—	`conf`	Ranked Tiling. ECML/PKDD (2) Thanh Le Van, Matthijs van Leeuwen, Siegfried Nijssen, Ana Carolina Fierro, Kathleen Marchal, Luc De Raedt
2014	A	`conf`	Relational Regularization and Feature Ranking. SDM Fabrizio Costa, Mathias Verbeke, Luc De Raedt
2014	A*	`conf`	Relational object tracking and learning. ICRA Davide Nitti, Tinne De Laet, Luc De Raedt
2014	J	`jnl`	There are plenty of places like home: Using relational representations in hierarchies for distance-based image understanding. Neurocomputing Laura Antanas, Martijn van Otterlo, José Oramas Mogrovejo, Tinne Tuytelaars, Luc De Raedt
2014	A	`conf`	Towards cautious collective inference for object verification. WACV José Oramas M., Luc De Raedt, Tinne Tuytelaars
2014	J	`jnl`	kLog: A language for logical and relational learning with kernels. Artif. Intell. Paolo Frasconi, Fabrizio Costa, Luc De Raedt, Kurt De Grave
2014	—	`conf`	kLogNLP: Graph Kernel-based Relational Learning of Natural Language. ACL (System Demonstrations) Mathias Verbeke, Paolo Frasconi, Kurt De Grave, Fabrizio Costa, Luc De Raedt
2013	C	`conf`	10 Years of Probabilistic Querying - What Next? ADBIS Martin Theobald, Luc De Raedt, Maximilian Dylla, Angelika Kimmig, Iris Miliaraki
2013	A	`conf`	A particle filter for hybrid relational domains. IROS Davide Nitti, Tinne De Laet, Luc De Raedt
2013	A	`conf`	A relational kernel-based approach to scene classification. WACV Laura Antanas, McElory Hoffmann, Paolo Frasconi, Tinne Tuytelaars, Luc De Raedt
2013	B	`conf`	Active Preference Learning for Ranking Patterns. ICTAI Vladimir Dzyuba, Matthijs van Leeuwen, Siegfried Nijssen, Luc De Raedt
2013	A*	`conf`	Allocentric Pose Estimation. ICCV José Oramas M., Luc De Raedt, Tinne Tuytelaars
2013	J	`jnl`	Inference and learning in probabilistic logic programs using weighted Boolean formulas CoRR Daan Fierens, Guy Van den Broeck, Joris Renkens, Dimitar Sht. Shterionov, Bernd Gutmann, Ingo Thon, Gerda Janssens, Luc De Raedt
2013	C	`conf`	MCMC Estimation of Conditional Probabilities in Probabilistic Programming Languages. ECSQARU Bogdan Moldovan, Ingo Thon, Jesse Davis, Luc De Raedt
2013	J	`jnl`	Mining closed patterns in relational, graph and network data. Ann. Math. Artif. Intell. Gemma C. Garriga, Roni Khardon, Luc De Raedt
2013	A*	`conf`	MiningZinc: A Modeling Language for Constraint-Based Mining. IJCAI Tias Guns, Anton Dries, Guido Tack, Siegfried Nijssen, Luc De Raedt
2013	J	`jnl`	Probabilistic Programming Concepts. CoRR Luc De Raedt, Angelika Kimmig
2013	—	`conf`	Statistical Relational Learning using ProbLog. KNOW@LOD Luc De Raedt
2013	—	`conf`	The MiningZinc Framework for Constraint-Based Itemset Mining. ICDM Workshops Tias Guns, Anton Dries, Guido Tack, Siegfried Nijssen, Luc De Raedt
2013	J	`jnl`	k-Pattern Set Mining under Constraints. IEEE Trans. Knowl. Data Eng. Tias Guns, Siegfried Nijssen, Luc De Raedt
2012	—	`conf`	A Particle Filter for Probabilistic Dynamic Relational Domains. StarAI@UAI Davide Nitti, Tinne De Laet, McElory Hoffmann, Ingo Thon, Guy Van den Broeck, Luc De Raedt
2012	—	`conf`	A Relational Distance-based Framework for Hierarchical Image Understanding. ICPRAM (2) Laura Antanas, Martijn van Otterlo, José Oramas M., Tinne Tuytelaars, Luc De Raedt
2012	—	`conf`	A Relational Kernel-Based Framework for Hierarchical Image Understanding. SSPR/SPR Laura Antanas, Paolo Frasconi, Fabrizio Costa, Tinne Tuytelaars, Luc De Raedt
2012	—	`conf`	A Statistical Relational Learning Approach to Identifying Evidence Based Medicine Categories. EMNLP-CoNLL Mathias Verbeke, Vincent Van Asch, Roser Morante, Paolo Frasconi, Walter Daelemans, Luc De Raedt
2012	J	`jnl`	Algebraic Model Counting CoRR Angelika Kimmig, Guy Van den Broeck, Luc De Raedt
2012	—	`ch.`	BiQL: A Query Language for Analyzing Information Networks. Bisociative Knowledge Discovery Anton Dries, Siegfried Nijssen, Luc De Raedt
2012	B	`conf`	Declarative Modeling for Machine Learning and Data Mining. ALT Luc De Raedt
2012	B	`conf`	Declarative Modeling for Machine Learning and Data Mining. Discovery Science Luc De Raedt
2012	C	`conf`	Declarative Modeling for Machine Learning and Data Mining. ICFCA Luc De Raedt
2012	—	`conf`	Declarative Modeling for Machine Learning and Data Mining. ECML/PKDD (1) Luc De Raedt
2012	A	`ed.`	ECAI 2012 - 20th European Conference on Artificial Intelligence. Including Prestigious Applications of Artificial Intelligence (PAIS-2012) System Demonstrations Track, Montpellier, France, August 27-31 , 2012 ECAI Luc De Raedt, Christian Bessiere, Didier Dubois, Patrick Doherty, Paolo Frasconi, Fredrik Heintz, Peter J. F. Lucas
2012	J	`jnl`	ILP turns 20 - Biography and future challenges. Mach. Learn. Stephen H. Muggleton, Luc De Raedt, David Poole, Ivan Bratko, Peter A. Flach, Katsumi Inoue, Ashwin Srinivasan
2012	J	`jnl`	Inference in Probabilistic Logic Programs using Weighted CNF's CoRR Daan Fierens, Guy Van den Broeck, Ingo Thon, Bernd Gutmann, Luc De Raedt
2012	A*	`conf`	Learning relational affordance models for robots in multi-object manipulation tasks. ICRA Bogdan Moldovan, Plinio Moreno, Martijn van Otterlo, José Santos-Victor, Luc De Raedt
2012	—	`conf`	Mining Local Staircase Patterns in Noisy Data. ICDM Workshops Thanh Le Van, Ana Carolina Fierro, Tias Guns, Matthijs van Leeuwen, Siegfried Nijssen, Luc De Raedt, Kathleen Marchal
2012	—	`ch.`	Patterns and Logic for Reasoning with Networks. Bisociative Knowledge Discovery Angelika Kimmig, Esther Galbrun, Hannu Toivonen, Luc De Raedt
2012	J	`jnl`	kLog: A Language for Logical and Relational Learning with Kernels CoRR Paolo Frasconi, Fabrizio Costa, Luc De Raedt, Kurt De Grave
2011	A*	`conf`	An Algebraic Prolog for Reasoning about Possible Worlds. AAAI Angelika Kimmig, Guy Van den Broeck, Luc De Raedt
2011	J	`jnl`	Constraint Programming meets Machine Learning and Data Mining (Dagstuhl Seminar 11201). Dagstuhl Reports Luc De Raedt, Siegfried Nijssen, Barry O'Sullivan, Pascal Van Hentenryck
2011	—	`conf`	Declarative Heuristic Search for Pattern Set Mining. ICDM Workshops Tias Guns, Siegfried Nijssen, Albrecht Zimmermann, Luc De Raedt
2011	J	`jnl`	Effective feature construction by maximum common subgraph sampling. Mach. Learn. Leander Schietgat, Fabrizio Costa, Jan Ramon, Luc De Raedt
2011	—	`conf`	Evaluating Pattern Set Mining Strategies in a Constraint Programming Framework. PAKDD (2) Tias Guns, Siegfried Nijssen, Luc De Raedt
2011	J	`jnl`	Guest editorial to the special issue on inductive logic programming, mining and learning in graphs and statistical relational learning. Mach. Learn. Hendrik Blockeel, Karsten M. Borgwardt, Luc De Raedt, Pedro M. Domingos, Kristian Kersting, Xifeng Yan
2011	A	`conf`	Inference in Probabilistic Logic Programs using Weighted CNF's. UAI Daan Fierens, Guy Van den Broeck, Ingo Thon, Bernd Gutmann, Luc De Raedt
2011	J	`jnl`	Itemset mining: A constraint programming perspective. Artif. Intell. Tias Guns, Siegfried Nijssen, Luc De Raedt
2011	B	`conf`	Kernel-Based Logical and Relational Learning with kLog for Hedge Cue Detection. ILP Mathias Verbeke, Paolo Frasconi, Vincent Van Asch, Roser Morante, Walter Daelemans, Luc De Raedt
2011	—	`conf`	Learning the Parameters of Probabilistic Logic Programs from Interpretations. ECML/PKDD (1) Bernd Gutmann, Ingo Thon, Luc De Raedt
2011	A*	`conf`	Lifted Probabilistic Inference by First-Order Knowledge Compilation. IJCAI Guy Van den Broeck, Nima Taghipour, Wannes Meert, Jesse Davis, Luc De Raedt
2011	J	`jnl`	Logical Hidden Markov Models CoRR Luc De Raedt, Kristian Kersting, Tapani Raiko
2011	J	`jnl`	On the implementation of the probabilistic logic programming language ProbLog. Theory Pract. Log. Program. Angelika Kimmig, Bart Demoen, Luc De Raedt, Vítor Santos Costa, Ricardo Rocha
2011	B	`conf`	Relational Learning for Spatial Relation Extraction from Natural Language. ILP Parisa Kordjamshidi, Paolo Frasconi, Martijn van Otterlo, Marie-Francine Moens, Luc De Raedt
2011	—	`conf`	Statistical Relational Learning of Object Affordances for Robotic Manipulation. ILP (Late Breaking Papers) Bogdan Moldovan, Martijn van Otterlo, Luc De Raedt, Plinio Moreno, José Santos-Victor
2011	J	`jnl`	Stochastic relational processes: Efficient inference and applications. Mach. Learn. Ingo Thon, Niels Landwehr, Luc De Raedt
2011	J	`jnl`	The Magic of Logical Inference in Probabilistic Programming CoRR Bernd Gutmann, Ingo Thon, Angelika Kimmig, Maurice Bruynooghe, Luc De Raedt
2011	J	`jnl`	The magic of logical inference in probabilistic programming. Theory Pract. Log. Program. Bernd Gutmann, Ingo Thon, Angelika Kimmig, Maurice Bruynooghe, Luc De Raedt
2011	C	`conf`	Towards Programming Languages for Machine Learning and Data Mining (Extended Abstract). ISMIS Luc De Raedt, Siegfried Nijssen
2010	—	`ch.`	A Theory of Inductive Query Answering. Inductive Databases and Constraint-Based Data Mining Luc De Raedt, Manfred Jaeger, Sau Dan Lee, Heikki Mannila
2010	—	`ch.`	About Knowledge and Inference in Logical and Relational Learning. Advances in Machine Learning II Luc De Raedt
2010	A*	`conf`	Constraint Programming for Data Mining and Machine Learning. AAAI Luc De Raedt, Tias Guns, Siegfried Nijssen
2010	A*	`conf`	DTProbLog: A Decision-Theoretic Probabilistic Prolog. AAAI Guy Van den Broeck, Ingo Thon, Martijn van Otterlo, Luc De Raedt
2010	B	`conf`	Extending ProbLog with Continuous Distributions. ILP Bernd Gutmann, Manfred Jaeger, Luc De Raedt
2010	J	`jnl`	Fast learning of relational kernels. Mach. Learn. Niels Landwehr, Andrea Passerini, Luc De Raedt, Paolo Frasconi
2010	B	`ed.`	Inductive Logic Programming, 19th International Conference, ILP 2009, Leuven, Belgium, July 02-04, 2009. Revised Papers ILP Luc De Raedt
2010	—	`ch.`	Inductive Logic Programming. Encyclopedia of Machine Learning Luc De Raedt
2010	—	`ch.`	Logic of Generality. Encyclopedia of Machine Learning Luc De Raedt
2010	J	`jnl`	Mining Predictive k-CNF Expressions. IEEE Trans. Knowl. Data Eng. Anton Dries, Luc De Raedt, Siegfried Nijssen
2010	—	`ch.`	Multi-Relational Data Mining. Encyclopedia of Machine Learning Luc De Raedt
2010	B	`conf`	Not Far Away from Home: A Relational Distance-Based Approach to Understanding Images of Houses. ILP Laura Antanas, Martijn van Otterlo, José Oramas M., Tinne Tuytelaars, Luc De Raedt
2010	J	`jnl`	On the Implementation of the Probabilistic Logic Programming Language ProbLog CoRR Angelika Kimmig, Bart Demoen, Luc De Raedt, Vítor Santos Costa, Ricardo Rocha
2010	A	`conf`	ProbLog Technology for Inference in a Probabilistic First Order Logic. ECAI Maurice Bruynooghe, Theofrastos Mantadelis, Angelika Kimmig, Bernd Gutmann, Joost Vennekens, Gerda Janssens, Luc De Raedt
2010	—	`ch.`	Probabilistic Inductive Querying Using ProbLog. Inductive Databases and Constraint-Based Data Mining Luc De Raedt, Angelika Kimmig, Bernd Gutmann, Kristian Kersting, Vítor Santos Costa, Hannu Toivonen
2010	B	`conf`	Probabilistic Rule Learning. ILP Luc De Raedt, Ingo Thon
2010	—	`ch.`	Statistical Relational Learning. Encyclopedia of Machine Learning Luc De Raedt, Kristian Kersting
2009	A	`conf`	A query language for analyzing networks. CIKM Anton Dries, Siegfried Nijssen, Luc De Raedt
2009	—	`conf`	An Exercise with Statistical Relational Learning Systems. MLG/SRL@ILP Maurice Bruynooghe, Daan Fierens, Bernd Gutmann, Angelika Kimmig, Niels Landwehr, Wannes Meert, Ingo Thon, Luc De Raedt
2009	J	`jnl`	Cluster-grouping: from subgroup discovery to clustering. Mach. Learn. Albrecht Zimmermann, Luc De Raedt
2009	—	`conf`	Constraint Programming for Data Mining. EGC Luc De Raedt
2009	A*	`conf`	Correlated itemset mining in ROC space: a constraint programming approach. KDD Siegfried Nijssen, Tias Guns, Luc De Raedt
2009	J	`jnl`	Deriving distance metrics from generality relations. Pattern Recognit. Lett. Luc De Raedt, Jan Ramon
2009	—	`conf`	From ProbLog to First Order Logic: A First Exploration. MLG/SRL@ILP Joost Vennekens, Angelika Kimmig, Theofrastos Mantadelis, Bernd Gutmann, Luc De Raedt, Maurice Bruynooghe
2009	A	`conf`	Grammar Mining. SDM Siegfried Nijssen, Luc De Raedt
2009	A*	`conf`	Local Query Mining in a Probabilistic Prolog. IJCAI Angelika Kimmig, Luc De Raedt
2009	—	`conf`	Maximum Common Subgraph Mining: A Fast and Effective Approach towards Feature Generation. MLG/SRL@ILP Leander Schietgat, Fabrizio Costa, Jan Ramon, Luc De Raedt
2009	B	`conf`	Probabilistic Logic Learning - A Tutorial Abstract. ICLP Luc De Raedt
2009	—	`ed.`	Proceedings of the Joint 7th Workshop on Mining and Learning with Graphs and the 6th International Workshop on Statistical Relational Learning, MLG/SRL@ILP 2009, Leuven, Belgium, July 2-4, 2009 MLG/SRL@ILP Hendrik Blockeel, Karsten M. Borgwardt, Luc De Raedt, Pedro M. Domingos, Kristian Kersting, Xifeng Yan
2009	C	`conf`	The Logic of Learning. ICFCA Luc De Raedt
2009	B	`conf`	Towards Clausal Discovery for Stream Mining. ILP Anton Dries, Luc De Raedt
2008	—	`conf`	08041 Abstracts Collection -- Recurrent Neural Networks - Models, Capacities, and Applications. Recurrent Neural Networks Luc De Raedt, Barbara Hammer, Pascal Hitzler, Wolfgang Maass
2008	—	`conf`	08041 Summary -- Recurrent Neural Networks - Models, Capacities, and Applications. Recurrent Neural Networks Luc De Raedt, Barbara Hammer, Pascal Hitzler, Wolfgang Maass
2008	—	`conf`	A Simple Model for Sequences of Relational State Descriptions. ECML/PKDD (2) Ingo Thon, Niels Landwehr, Luc De Raedt
2008	B	`conf`	Active Learning for High Throughput Screening. Discovery Science Kurt De Grave, Jan Ramon, Luc De Raedt
2008	J	`jnl`	An experimental evaluation of simplicity in rule learning. Artif. Intell. Ulrich Rückert, Luc De Raedt
2008	—	`ch.`	Basic Principles of Learning Bayesian Logic Programs. Probabilistic Inductive Logic Programming Kristian Kersting, Luc De Raedt
2008	J	`jnl`	Compressing probabilistic Prolog programs. Mach. Learn. Luc De Raedt, Kristian Kersting, Angelika Kimmig, Kate Revoredo, Hannu Toivonen
2008	A*	`conf`	Constraint programming for itemset mining. KDD Luc De Raedt, Tias Guns, Siegfried Nijssen
2008	—	`conf`	Logic, Probability and Learning, or an Introduction to Statistical Relational Learning. SBIA Luc De Raedt
2008	—	`conf`	Logical and Relational Learning. SBIA Luc De Raedt
2008	—	`book`	Logical and relational learning. Luc De Raedt
2008	B	`conf`	On the Efficient Execution of ProbLog Programs. ICLP Angelika Kimmig, Vítor Santos Costa, Ricardo Rocha, Bart Demoen, Luc De Raedt
2008	—	`conf`	Parameter Learning in Probabilistic Databases: A Least Squares Approach. MLG@ICML Bernd Gutmann, Angelika Kimmig, Luc De Raedt, Kristian Kersting
2008	—	`conf`	Parameter Learning in Probabilistic Databases: A Least Squares Approach. ECML/PKDD (1) Bernd Gutmann, Angelika Kimmig, Kristian Kersting, Luc De Raedt
2008	—	`book`	Probabilistic Inductive Logic Programming - Theory and Applications Probabilistic Inductive Logic Programming Luc De Raedt, Paolo Frasconi, Kristian Kersting, Stephen H. Muggleton
2008	—	`ch.`	Probabilistic Inductive Logic Programming. Probabilistic Inductive Logic Programming Luc De Raedt, Kristian Kersting
2008	—	`ed.`	Probabilistic, Logical and Relational Learning - A Further Synthesis, 15.04. - 20.04.2007 Probabilistic, Logical and Relational Learning - A Further Synthesis Luc De Raedt, Thomas G. Dietterich, Lise Getoor, Kristian Kersting, Stephen H. Muggleton
2008	—	`ed.`	Recurrent Neural Networks - Models, Capacities, and Applications, 20.01. - 25.01.2008 Recurrent Neural Networks Luc De Raedt, Barbara Hammer, Pascal Hitzler, Wolfgang Maass
2008	—	`ch.`	Relational Sequence Learning. Probabilistic Inductive Logic Programming Kristian Kersting, Luc De Raedt, Bernd Gutmann, Andreas Karwath, Niels Landwehr
2008	J	`jnl`	Relational Transformation-based Tagging for Activity Recognition. Fundam. Informaticae Niels Landwehr, Bernd Gutmann, Ingo Thon, Luc De Raedt, Matthai Philipose
2007	—	`conf`	07161 Abstracts Collection -- Probabilistic, Logical and Relational Learning - A Further Synthesis. Probabilistic, Logical and Relational Learning - A Further Synthesis Luc De Raedt, Thomas G. Dietterich, Lise Getoor, Kristian Kersting, Stephen H. Muggleton
2007	A	`conf`	Constraint-Based Pattern Set Mining. SDM Luc De Raedt, Albrecht Zimmermann
2007	J	`jnl`	Integrating Naïve Bayes and FOIL. J. Mach. Learn. Res. Niels Landwehr, Kristian Kersting, Luc De Raedt
2007	J	`jnl`	Learning to transfer optimal navigation policies. Adv. Robotics Kristian Kersting, Christian Plagemann, Alexandru Cocora, Wolfram Burgard, Luc De Raedt
2007	—	`ch.`	Mining Structure-Activity Relations in Biological Neural Networks using NeuronRank. Perspectives of Neural-Symbolic Integration Tayfun Gürel, Luc De Raedt, Stefan Rotter
2007	A*	`conf`	On Mining Closed Sets in Multi-Relational Data. IJCAI Gemma C. Garriga, Roni Khardon, Luc De Raedt
2007	B	`conf`	Predicting Spike Activity in Neuronal Cultures. IJCNN Tayfun Gürel, Ulrich Egert, Steffen Kandler, Luc De Raedt, Stefan Rotter
2007	—	`conf`	ProbLog and its Application to Link Mining in Biological Networks. MLG Luc De Raedt
2007	A*	`conf`	ProbLog: A Probabilistic Prolog and Its Application in Link Discovery. IJCAI Luc De Raedt, Angelika Kimmig, Hannu Toivonen
2007	—	`conf`	Probabilistic Explanation Based Learning. ECML Angelika Kimmig, Luc De Raedt, Hannu Toivonen
2007	J	`jnl`	Ranking neurons for mining structure-activity relations in biological neural networks: NeuronRank. Neurocomputing Tayfun Gürel, Luc De Raedt, Stefan Rotter
2007	C	`conf`	Statistical Relational Learning - A Logical Approach (Abstract of Invited Talk). NeSy Luc De Raedt
2007	A*	`conf`	r-grams: Relational Grams. IJCAI Niels Landwehr, Luc De Raedt
2006	J	`jnl`	A Bottom-up approach to Grid-Computing at a University: the Black-Forest-Grid Initiative. Prax. Inf.verarb. Kommun. Rolf Backofen, Hans-Gunther Borrmann, Werner Deck, Andreas Dedner, Luc De Raedt, Klaus Desch, Markus Diesmann, Martin Geier, Andreas Greiner, Wolfgang R. Hess, Josef Honerkamp, Stefan Jankowski, Ingo Krossing, Andreas W. Liehr, Andreas Karwath, Robert Klöfkorn, Raphaël Pesché, Tobias C. Potjans, Michael C. Röttger, Lars Schmidt-Thieme, Gerhard Schneider, Björn Voß, Bernd Wiebelt, Peter Wienemann, Volker-Henning Winterer
2006	—	`conf`	Don't Be Afraid of Simpler Patterns. PKDD Björn Bringmann, Albrecht Zimmermann, Luc De Raedt, Siegfried Nijssen
2006	B	`conf`	Frequent Hypergraph Mining. ILP Tamás Horváth, Björn Bringmann, Luc De Raedt
2006	—	`conf`	IQL: A Proposal for an Inductive Query Language. KDID Siegfried Nijssen, Luc De Raedt
2006	J	`jnl`	Kernels on Prolog Proof Trees: Statistical Learning in the ILP Setting. J. Mach. Learn. Res. Andrea Passerini, Paolo Frasconi, Luc De Raedt
2006	A	`conf`	Learning Relational Navigation Policies. IROS Alexandru Cocora, Kristian Kersting, Christian Plagemann, Wolfram Burgard, Luc De Raedt
2006	J	`jnl`	Learning Relational Navigation Policies. Künstliche Intell. Alexandru Cocora, Kristian Kersting, Wolfram Burgard, Luc De Raedt, Christian Plagemann
2006	J	`jnl`	Logical Hidden Markov Models. J. Artif. Intell. Res. Kristian Kersting, Luc De Raedt, Tapani Raiko
2006	—	`conf`	Mining Bi-sets in Numerical Data. KDID Jérémy Besson, Céline Robardet, Luc De Raedt, Jean-François Boulicaut
2006	—	`ed.`	Probabilistic, Logical and Relational Learning - Towards a Synthesis, 30. January - 4. February 2005 Probabilistic, Logical and Relational Learning Luc De Raedt, Thomas G. Dietterich, Lise Getoor, Stephen H. Muggleton
2006	B	`conf`	Revising Probabilistic Prolog Programs. ILP Luc De Raedt, Kristian Kersting, Angelika Kimmig, Kate Revoredo, Hannu Toivonen
2006	J	`jnl`	SMIREP: Predicting Chemical Activity from SMILES. J. Chem. Inf. Model. Andreas Karwath, Luc De Raedt
2006	A*	`conf`	kFOIL: Learning Simple Relational Kernels. AAAI Niels Landwehr, Andrea Passerini, Luc De Raedt, Paolo Frasconi
2005	—	`conf`	05051 Abstracts Collection - Probabilistic, Logical and Relational Learning - Towards a Synthesis. Probabilistic, Logical and Relational Learning Luc De Raedt, Thomas G. Dietterich, Lise Getoor, Stephen H. Muggleton
2005	—	`conf`	05051 Executive Summary - Probabilistic, Logical and Relational Learning - Towards a Synthesis. Probabilistic, Logical and Relational Learning Luc De Raedt, Thomas G. Dietterich, Lise Getoor, Stephen H. Muggleton
2005	J	`jnl`	Advances in Mining Graphs, Trees and Sequences. Fundam. Informaticae Takashi Washio, Luc De Raedt, Joost N. Kok
2005	B	`conf`	CLASSIC'CL: An Integrated ILP System. Discovery Science Christian Stolle, Andreas Karwath, Luc De Raedt
2005	—	`ed.`	Constraint-Based Mining and Inductive Databases, European Workshop on Inductive Databases and Constraint Based Mining, Hinterzarten, Germany, March 11-13, 2004, Revised Selected Papers Constraint-Based Mining and Inductive Databases Jean-François Boulicaut, Luc De Raedt, Heikki Mannila
2005	—	`conf`	Kernels on Prolog Proof Trees: Statistical Learning in the ILP Setting. AAIP Andrea Passerini, Paolo Frasconi, Luc De Raedt
2005	—	`conf`	Kernels on Prolog Proof Trees: Statistical Learning in the ILP Setting. Probabilistic, Logical and Relational Learning Andrea Passerini, Paolo Frasconi, Luc De Raedt
2005	A*	`ed.`	Machine Learning, Proceedings of the Twenty-Second International Conference (ICML 2005), Bonn, Germany, August 7-11, 2005 ICML Luc De Raedt, Stefan Wrobel
2005	—	`conf`	Statistical Relational Learning: An Inductive Logic Programming Perspective. PKDD Luc De Raedt
2005	A*	`conf`	Towards Learning Stochastic Logic Programs from Proof-Banks. AAAI Luc De Raedt, Kristian Kersting, Sunna Torge
2005	A*	`conf`	nFOIL: Integrating Naïve Bayes and FOIL. AAAI Niels Landwehr, Kristian Kersting, Luc De Raedt
2004	—	`conf`	An Efficient Algorithm for Mining String Databases Under Constraints. KDID Sau Dan Lee, Luc De Raedt
2004	A*	`conf`	Bellman goes relational. ICML Kristian Kersting, Martijn van Otterlo, Luc De Raedt
2004	—	`conf`	Cluster-Grouping: From Subgroup Discovery to Clustering. ECML Albrecht Zimmermann, Luc De Raedt
2004	A*	`conf`	Condensed Representations for Inductive Logic Programming. KR Luc De Raedt, Jan Ramon
2004	—	`ch.`	Constraint Based Mining of First Order Sequences in SeqLog. Database Support for Data Mining Applications Sau Dan Lee, Luc De Raedt
2004	B	`conf`	CorClass: Correlated Association Rule Mining for Classification. Discovery Science Albrecht Zimmermann, Luc De Raedt
2004	J	`jnl`	Data Mining and Machine Learning Techniques for the Identification of Mutagenicity Inducing Substructures and Structure Activity Relationships of Noncongeneric Compounds. J. Chem. Inf. Model. Christoph Helma, Tobias Cramer, Stefan Kramer, Luc De Raedt
2004	—	`conf`	Inductive Querying for Discovering Subgroups and Clusters. Constraint-Based Mining and Inductive Databases Albrecht Zimmermann, Luc De Raedt
2004	B	`conf`	Logical Markov Decision Programs and the Convergence of Logical TD(lambda). ILP Kristian Kersting, Luc De Raedt
2004	B	`conf`	Predictive Graph Mining. Discovery Science Andreas Karwath, Luc De Raedt
2004	B	`conf`	Probabilistic Inductive Logic Programming. ALT Luc De Raedt, Kristian Kersting
2004	B	`conf`	Towards Optimizing Conjunctive Inductive Queries. PAKDD Johannes Fischer, Luc De Raedt
2004	—	`ch.`	Towards Query Evaluation in Inductive Databases Using Version Spaces. Database Support for Data Mining Applications Luc De Raedt
2003	A*	`conf`	An Algebra for Inductive Query Evaluation. ICDM Sau Dan Lee, Luc De Raedt
2003	—	`conf`	An Algebra for Inductive Query Evaluation. KDID Sau Dan Lee, Luc De Raedt
2003	J	`jnl`	Multi-relational data mining: the current frontiers. SIGKDD Explor. Saso Dzeroski, Luc De Raedt
2003	J	`jnl`	Multirelational data mining 2003: workshop report. SIGKDD Explor. Saso Dzeroski, Luc De Raedt, Stefan Wrobel
2003	J	`jnl`	Probabilistic logic learning. SIGKDD Explor. Luc De Raedt, Kristian Kersting
2003	Misc	`conf`	Towards Discovering Structural Signatures of Protein Folds Based on Logical Hidden Markov Models. Pacific Symposium on Biocomputing Kristian Kersting, Tapani Raiko, Stefan Kramer, Luc De Raedt
2003	—	`conf`	Towards Optimizing Conjunctive Inductive Queries. KDID Johannes Fischer, Luc De Raedt
2002	J	`jnl`	A Perspective on Inductive Databases. SIGKDD Explor. Luc De Raedt
2002	A*	`conf`	A Theory of Inductive Query Answering. ICDM Luc De Raedt, Manfred Jaeger, Sau Dan Lee, Heikki Mannila
2002	—	`conf`	Constraint Based Mining of First Order Sequences in SeqLog. KDID Sau Dan Lee, Luc De Raedt
2002	—	`conf`	Data Mining as Constraint Logic Programming. Computational Logic: Logic Programming and Beyond Luc De Raedt
2002	—	`conf`	Logical Hidden Markov Models (Extendes abstract). Probabilistic Graphical Models Kristian Kersting, Tapani Raiko, Luc De Raedt
2002	J	`jnl`	Multi-Relational Data Mining: a Workshop Report. SIGKDD Explor. Saso Dzeroski, Luc De Raedt
2002	—	`conf`	Phase Transitions and Stochastic Local Search in k-Term DNF Learning. ECML Ulrich Rückert, Stefan Kramer, Luc De Raedt
2001	B	`conf`	Adaptive Bayesian Logic Programs. ILP Kristian Kersting, Luc De Raedt
2001	J	`jnl`	Bayesian Logic Programs CoRR Kristian Kersting, Luc De Raedt
2001	A*	`conf`	Feature Construction with Version Spaces for Biochemical Applications. ICML Stefan Kramer, Luc De Raedt
2001	—	`conf`	How to Upgrade Propositional Learners to First Order Logic: A Case Study. Machine Learning and Its Applications Wim Van Laer, Luc De Raedt
2001	—	`ed.`	Machine Learning: EMCL 2001, 12th European Conference on Machine Learning, Freiburg, Germany, September 5-7, 2001, Proceedings ECML Luc De Raedt, Peter A. Flach
2001	A*	`conf`	Molecular feature mining in HIV data. KDD Stefan Kramer, Luc De Raedt, Christoph Helma
2001	—	`ed.`	Principles of Data Mining and Knowledge Discovery, 5th European Conference, PKDD 2001, Freiburg, Germany, September 3-5, 2001, Proceedings PKDD Luc De Raedt, Arno Siebes
2001	J	`jnl`	Relational Reinforcement Learning. Mach. Learn. Saso Dzeroski, Luc De Raedt, Kurt Driessens
2001	A*	`conf`	The Levelwise Version Space Algorithm and its Application to Molecular Fragment Finding. IJCAI Luc De Raedt, Stefan Kramer
2001	B	`conf`	Towards Combining Inductive Logic Programming with Bayesian Networks. ILP Kristian Kersting, Luc De Raedt
2000	B	`conf`	A Logical Database Mining Query Language. ILP Luc De Raedt
2000	J	`jnl`	AI Research in the Benelux - Guest Editorial. AI Commun. Luc De Raedt, Johannes A. La Poutré, Floor Verdenius
2000	—	`conf`	Bayesian Logic Programs. ILP Work-in-progress reports Kristian Kersting, Luc De Raedt
2000	J	`jnl`	Benelearn: The First 10 Years. AI Commun. Luc De Raedt, Maarten van Someren
2000	J	`jnl`	Scaling Up Inductive Logic Programming by Learning from Interpretations CoRR Hendrik Blockeel, Luc De Raedt, Nico Jacobs, Bart Demoen
2000	J	`jnl`	Top-down induction of clustering trees CoRR Hendrik Blockeel, Luc De Raedt, Jan Ramon
1999	—	`ch.`	A Perspective on Inductive Logic Programming. The Logic Programming Paradigm Luc De Raedt
1999	—	`conf`	Database Mining and Inductive Logic Programming. JFPLC Luc De Raedt
1999	B	`conf`	Generalizing Refinement Operators to Learn Prenex Conjunctive Normal Forms. ILP Shan-Hwei Nienhuys-Cheng, Wim Van Laer, Jan Ramon, Luc De Raedt
1999	B	`conf`	Instance Based Function Learning. ILP Jan Ramon, Luc De Raedt
1999	—	`conf`	Relational Learning and Inductive Logic Programming Made Easy Abstract of Tutorial. PKDD Luc De Raedt, Hendrik Blockeel
1999	J	`jnl`	Scaling Up Inductive Logic Programming by Learning from Interpretations. Data Min. Knowl. Discov. Hendrik Blockeel, Luc De Raedt, Nico Jacobs, Bart Demoen
1998	Misc	`conf`	An Inductive Logic Programming Query Language for Database Mining. AISC Luc De Raedt
1998	B	`conf`	Attribute-Value Learning Versus Inductive Logic Programming: The Missing Links (Extended Abstract). ILP Luc De Raedt
1998	C	`conf`	Inductive Verification and Validation of the KULRoT RoboCup Team. RoboCup Kurt Driessens, Nico Jacobs, Nathalie Cossement, Patrick Monsieurs, Luc De Raedt
1998	—	`conf`	Inductive verification and validation of multi agent systems. EUROVAV Nico Jacobs, Kurt Driessens, Luc De Raedt
1998	J	`jnl`	Isidd: An Interactive System for Inductive Database Design. Appl. Artif. Intell. Hendrik Blockeel, Luc De Raedt
1998	A*	`conf`	Relational Reinforcement Learning. ICML Saso Dzeroski, Luc De Raedt, Hendrik Blockeel
1998	B	`conf`	Relational Reinforcement Learning. ILP Saso Dzeroski, Luc De Raedt, Hendrik Blockeel
1998	A*	`conf`	Top-Down Induction of Clustering Trees. ICML Hendrik Blockeel, Luc De Raedt, Jan Ramon
1998	J	`jnl`	Top-Down Induction of First-Order Logical Decision Trees. Artif. Intell. Hendrik Blockeel, Luc De Raedt
1998	B	`conf`	Using ILP-Systems for Verification and Validation of Multi-agent Systems. ILP Nico Jacobs, Kurt Driessens, Luc De Raedt
1997	J	`jnl`	Artificial Intelligence in Belgium and the BeNeLux: Past and Future. AI Commun. Luc De Raedt
1997	J	`jnl`	Clausal Discovery. Mach. Learn. Luc De Raedt, Luc Dehaspe
1997	J	`jnl`	Logical Settings for Concept-Learning. Artif. Intell. Luc De Raedt
1997	B	`conf`	Lookahead and Discretization in ILP. ILP Hendrik Blockeel, Luc De Raedt
1997	—	`conf`	Machine Learning for Verification and Validation. EUROVAV Luc De Raedt
1997	B	`conf`	Mining Association Rules in Multiple Relations. ILP Luc Dehaspe, Luc De Raedt
1997	C	`conf`	On Multi-class Problems and Discretization in Inductive Logic Programming. ISMIS Wim Van Laer, Luc De Raedt, Saso Dzeroski
1997	—	`conf`	Theta-Subsumption for Structural Matching. ECML Luc De Raedt, Peter Idestam-Almquist, Gunther Sablon
1997	B	`conf`	Using Logical Decision Trees for Clustering. ILP Luc De Raedt, Hendrik Blockeel
1996	B	`conf`	Analysis and Prediction of Piano Performances Using Inductive Logic Programming. Inductive Logic Programming Workshop Erika Van Baelen, Luc De Raedt
1996	C	`conf`	DLAB: A Declarative Language Bias Formalism. ISMIS Luc Dehaspe, Luc De Raedt
1996	C	`conf`	Inductive Database Design. ISMIS Hendrik Blockeel, Luc De Raedt
1996	J	`jnl`	Multiple Predicate Learning in Two Inductive Logic Programming Settings. Log. J. IGPL Luc De Raedt, Nada Lavrac
1996	C	`conf`	PAC-Learning Logic Programs under the Closed-World Assumption. ISMIS Luc De Raedt
1996	B	`conf`	Relational Knowledge Discovery in Databases. Inductive Logic Programming Workshop Hendrik Blockeel, Luc De Raedt
1995	J	`jnl`	Declarative Bias for Specific-to-General ILP Systems. Mach. Learn. Hilde Adé, Luc De Raedt, Maurice Bruynooghe
1995	A*	`conf`	Forgetting and Compacting data in Concept Learning. IJCAI Gunther Sablon, Luc De Raedt
1995	B	`conf`	Inductive Constraint Logic. ALT Luc De Raedt, Wim Van Laer
1995	J	`jnl`	Inductive Logic Programming: A Survey of European Research. AI Commun. Nada Lavrac, Luc De Raedt
1994	—	`conf`	Applications of a Logical Discovery Engine. KDD Workshop Wim Van Laer, Luc Dehaspe, Luc De Raedt
1994	J	`jnl`	First-Order jk-Clausal Theories are PAC-Learnable. Artif. Intell. Luc De Raedt, Saso Dzeroski
1994	J	`jnl`	Inductive Logic Programming: Theory and Methods. J. Log. Program. Stephen H. Muggleton, Luc De Raedt
1994	J	`jnl`	Iterative Versionspaces. Artif. Intell. Gunther Sablon, Luc De Raedt, Maurice Bruynooghe
1994	—	`ed.`	Machine Learning: ECML-94, European Conference on Machine Learning, Catania, Italy, April 6-8, 1994, Proceedings ECML Francesco Bergadano, Luc De Raedt
1994	C	`conf`	RUTH: an ILP Theory Revision System. ISMIS Hilde Adé, Bart Malfait, Luc De Raedt
1993	—	`conf`	A Brief Introduction to Inductive Logic Programming. ILPS Luc De Raedt
1993	A*	`conf`	A Theory of Clausal Discovery. IJCAI Luc De Raedt, Maurice Bruynooghe
1993	A*	`conf`	Multiple Predicate Learning. IJCAI Luc De Raedt, Nada Lavrac, Saso Dzeroski
1993	C	`conf`	The Many Faces of Inductive Logic Programming. ISMIS Luc De Raedt, Nada Lavrac
1992	J	`jnl`	A unifying framework for concept-learning algorithms. Knowl. Eng. Rev. Luc De Raedt, Maurice Bruynooghe
1992	J	`jnl`	Acquiring object-knowledge. J. Exp. Theor. Artif. Intell. Luc De Raedt, Johan Feyaerts, Maurice Bruynooghe
1992	J	`jnl`	Belief Updating from Integrity Constraints and Queries. Artif. Intell. Luc De Raedt, Maurice Bruynooghe
1992	J	`jnl`	Interactive Concept-Learning and Constructive Induction by Analogy. Mach. Learn. Luc De Raedt, Maurice Bruynooghe
1992	A	`conf`	Inverse Resolution in an Integrated Inductive-Deductive Learning System. ECAI Hilde Adé, Luc De Raedt, Maurice Bruynooghe
1991	—	`conf`	Acquiring Object-Knowledge for Learning Systems. EWSL Luc De Raedt, Johan Feyaerts, Maurice Bruynooghe
1991	—	`conf`	Integrity Constraints and Interactive Concept-Learning. ML Luc De Raedt, Maurice Bruynooghe, Bern Martens
1991	—	`conf`	Panel: Logic and Learnability. EWSL Luc De Raedt
1990	J	`jnl`	Indirect relevance and bias in inductive concept-learning. Knowl. Acquis. Luc De Raedt, Maurice Bruynooghe
1990	A	`conf`	On Negation and Three-Valued Logic in Interactive Concept-Learning. ECAI Luc De Raedt, Maurice Bruynooghe
1989	—	`conf`	Constructive Induction by Analogy. ML Luc De Raedt, Maurice Bruynooghe
1989	A*	`conf`	Explanation Based Program Transformation. IJCAI Maurice Bruynooghe, Luc De Raedt, Danny De Schreye
1989	—	`conf`	Generalizing Multiple Examples in Explanation Based Learning. AII Gunther Sablon, Luc De Raedt, Maurice Bruynooghe
1989	A*	`conf`	Towards Friendly Concept-Learners. IJCAI Luc De Raedt, Maurice Bruynooghe
1988	—	`conf`	On Interactive Concept-Learning and Assimilation. EWSL Luc De Raedt, Maurice Bruynooghe