Publications

2022

DeepStochLog: Neural Stochastic Logic Programming

Thomas Winters, Giuseppe Marra, Robin Manhaeve, Luc De Raedt

Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI) 2022
Domain-Lifted Sampling for Universal Two-Variable Logic and Extensions

Yuanhong Wang, Timothy Van Bremen, Yuyi Wang, Ondrej Kuzelka

Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI) 2022
Inference and Learning with Model Uncertainty in Probabilistic Logic Programs

Victor Verreet, Vincent Derkinderen, Pedro Zuidberg Dos Martires, Luc De Raedt

Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI) 2022
Automating Data Science: Prospects and Challenges

Tijl De Bie, Luc De Raedt, José Hernández-Orallo, Holger H. Hoos, Padhraic Smyth, Christopher K. I. Williams

Communications of the ACM Journal 2022

2021

Learning CNF Theories using MDL and Predicate Invention

Arcchit Jain, Clément Gautrais, Angelika Kimmig, Luc De Raedt

International Joint Conference on Artificial Intelligence (IJCAI) 2021
Context-Specific Likelihood Weighting

Nitesh Kumar, Ondrej Kuzelka

The 24th International Conference on Artificial Intelligence and Statistics 2021
An Automated Engineering Assistant: Learning Parsers for Technical Drawings

Dries Van Daele, Nicholas Decleyre, Herman Dubois, Wannes Meert

Innovative Applications of Artificial Intelligence Conference (IAAI) 2021
SpLyCI: Integrating Spreadsheets by Recognising and Solving Layout Constraints

Dirko Coetsee, Steve Kroon, McElory Hoffmann, Luc De Raedt

Symposium on Intelligent Data Analysis (IDA 2021) 2021
AVATAR — Automated feature wrangling for machine learning

Gust Verbruggen, Elia Van Wolputte, Sebastijan Dumancic, Luc De Raedt

Symposium on Intelligent Data Analysis (IDA) 2021
Muppets: Multipurpose Table Segmentation

Gust Verbruggen, Lidia Contreras-Ochando, Cèsar Ferri, José Hernández-Orallo, Luc De Raedt

Symposium on Intelligent Data Analysis (IDA) 2021
Hybrid probabilistic inference with logical and algebraic constraints: a survey

Paolo Morettin, Pedro Miguel Zuidberg Dos Martires, Samuel Kolb, Andrea Passerini

30th International Joint Conference on Artificial Intelligence (IJCAI) 2021
Democratizing Constraint Satisfaction Problems through Machine Learning

Mohit Kumar, Samuel Kolb, Clément Gautrais, Luc De Raedt

Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI) 2021
Approximate inference for Neural Probabilistic Logic Programming

Robin Manhaeve, Giuseppe Marra, Luc De Raedt

18th International Conference on Principles of Knowledge Representation and Reasoning 2021
Semantic programming by example with pre-trained models

Gust Verbruggen, Vu Le (MSR) and Sumit Gulwani (MSR)

Object-Oriented Programming Systems Languages & Applications conference 2021
The Effect of Hyperparameter Tuning on the Comparative Evaluation of Anomaly Detection Methods

Jonas Soenen, Elia Van Wolputte, Lorenzo Perini, Vincent Vercruyssen, Wannes Meert, Jesse Davis, Hendrik Blockeel

6th outlier detection and description workshop at KDD 2021
Neural Markov Logic Networks

Giuseppe Marra, Ondrej Kuzelka

The Conference on Uncertainty in Artificial Intelligence (UAI) 2021
SandSlide: Automatic Slideshow Normalization

Sieben Bocklandt, Gust Verbruggen, Thomas Winters

Proceedings of the 2021 16th International Conference on Document Analysis and Recognition (ICDAR) 2021
Learning Distributional Programs for Relational Autocompletion

Nitesh Kumar, Ondřej Kuželka, Luc De Raedt

Theory and Practice of Logic Programming 2021
Neural probabilistic logic programming in DeepProbLog

Robin Manhaeve, Sebastijan Dumancic, Angelika Kimmig, Thomas Demeester, Luc De Raedt

Artificial Intelligence 2021
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

European Machine Learning and Data Mining Conference (ECML-PKDD) 2021
Co-creating Platformer Levels with Constrained Adversarial Networks

Paolo Morettin, Andrea Passerini, Stefano Teso

2nd Workshop on Human-AI Co-Creation with Generative Models at the Intelligent User Interfaces 2021 conference (IUI) 2021
From Probabilistic NetKAT to ProbLog: New Algorithms for Inference and Learning in Probabilistic Networks

Birthe van den Berg, Timothy Van Bremen, Vincent Derkinderen, Angelika Kimmig, Tom Schrijvers, Luc De Raedt

International Conference on Probabilistic Programming (PROBPROG) 2021
Democratizing Constraint Satisfaction Problems through Machine Learning

Adem Kikaj, Samuel Kolb, Mohit Kumar, Gust Verbruggen, Luc De Raedt, Clément Gautrais

Workshop on Automating Data Science at European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD) 2021

2020

Learning MAX-SAT from Contextual Examples for Combinatorial Optimisation

Mohit Kumar, Samuel Kolb, Stefano Teso, Luc De Raedt

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence 2020
Learning Linear Programs from Data

Elias Arnold Schede, Samuel Kolb, Stefano Teso

2019 IEEE 31st International Conference on Tools with Artificial Intelligence (ICTAI) 2020
Efficient Generation of Structured Objects with Constrained Adversarial Networks

Luca Di Liello, Pierfrancesco Ardino, Jacopo Gobbi, Paolo Morettin, Stefano Teso, Andrea Passerini

Thirty-fourth Conference on Neural Information Processing Systems (NeurIPS) 2020
Probabilistic Inference with Algebraic Constraints: Theoretical Limits and Practical Approximations

Zhe Zeng, Paolo Morettin, Fanqi Yan, Antonio Vergari, Guy Van den Broeck

Thirty-fourth Conference on Neural Information Processing Systems (NeurIPS) 2020
From Statistical Relational to Neuro-Symbolic Artificial Intelligence

Luc De Raedt, Sebastijan Dumancic, Robin Manhaeve, Giuseppe Marra

Twenty-Ninth International Joint Conference on Artificial Intelligence (IJCAI) 2020
Widening for MDL-based Retail Signature Discovery

Clément Gautrais, Peggy Cellier, Matthijs van Leeuwen, Alexandre Termier

International Symposium on Intelligent Data Analysis (IDA) 2020
Missing value imputation with MERCS: a faster alternative to MissForest

Elia Van Wolputte, Hendrik Blockeel, Annalisa Appice (editor), Grigorios Tsoumakas (editor)

23rd International Conference on Discovery Science 2020
Ordering Variables for Weighted Model Integration

Vincent Derkinderen, Evert Heylen, Pedro Miguel Zuidberg Dos Martires, Samuel Kolb, Luc De Raedt

36th Conference on Uncertainty in Artificial Intelligence (UAI) 2020
Algebraic Circuits for Decision Theoretic Inference and Learning

Vincent Derkinderen, Luc De Raedt

24th European Conference on Artificial Intelligence (ECAI) 2020
Learning Weighted Model Integration Distributions

Paolo Morettin, Samuel Kolb, Stefano Teso, Andrea Passerini

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI) 2020
Symbolic Learning and Reasoning With Noisy Data for Probabilistic Anchoring

Pedro Zuidberg Dos Martires, Nitesh Kumar, Andreas Persson, Amy Loutfi, Luc De Raedt

Frontiers in Robotics and AI 2020
Semiring programming: A semantic framework for generalized sum product problems

Belle Vaishak, Luc De Raedt

INTERNATIONAL JOURNAL OF APPROXIMATE REASONING. ELSEVIER SCIENCE INC. 2020
Making deep neural networks right for the right scientific reasons by interacting with their explanations

Patrick Schramowski, Wolfgang Stammer, Stefano Teso, Anna Brugger, Franziska Herbert, Xiaoting Shao, Hans-Georg Luigs, Anne-Katrin Mahlein, Kristian Kersting

Nature Machine Intelligence 2020
onto2problog: A Probabilistic Ontology-Mediated Querying System using Probabilistic Logic Programming

Timothy Van Bremen, Anton Dries, Jean Christoph Jung

KI - Künstliche Intelligenz journal 2020
Human-Machine Collaboration for Democratizing Data Science

Clément Gautrais, Yann Dauxais, Stefano Teso, Samuel Kolb, Gust Verbruggen, Luc De Raedt

Chapter in a book: Human-Like Machine Intelligence 2020
Generalized Chronicles for Temporal Sequence Classification

Yann Dauxais, Thomas Guyet, Vincent Lemaire (Editor), Simon Malinowski (Editor), Anthony J Bagnall (Editor), (Editor), Romain Tavenard (Editor), Georgiana Ifrim (Editor)

ECML PKDD Workshop/ AALTD 2020
Monte Carlo Anti-Differentiation for Approximate Weighted Model Integration

Pedro Miguel Zuidberg Dos Martires, Samuel Kolb

Ninth International Workshop on Statistical Relational AI 2020

2019

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

Pedro Zuidberg Dos Martires, Anton Dries, Luc De Raedt

The AAAI Conference on Artificial Intelligence 2019
Automating Layout Synthesis with Constructive Preference Elicitation

Luca Erculiani, Paolo Dragone, Stefano Teso, Andrea Passerini

Joint European Conference on Machine Learning and Knowledge Discovery in Databases 2019
Explanatory Interactive Machine Learning

Stefano Teso, Kristian Kersting

AI Ethics and Society Conference 2019
Scalable Rule Learning in Probabilistic Knowledge Bases

Arcchit Jain, Tal Friedman, Ondrej Kuzelka, Guy Van den Broeck, Luc De Raedt

Automated Knowledge Base Construction conference 2019

https://github.com/arcchitjain/SafeLearner
Acquiring Integer Programs from Data

Mohit Kumar, Stefano Teso, Luc De Raedt

International Joint Conference on Artificial Intelligence (IJCAI) 2019
How to Exploit Structure while Solving Weighted Model Integration Problems

Pedro Zuidberg Dos Martires, Samuel Kolb, Luc De Raedt

The 35th Uncertainty in Artificial Intelligence Conference (UAI) 2019
The pywmi Framework and Toolbox for Probabilistic Inference using Weighted Model Integration

Samuel Kolb, Paolo Morettin, Pedro Zuidberg Dos Martires, Franscesco Sommavilla, Andrea Passerini, Roberto Sebastiani, Luc De Raedt

Twenty-Eighth International Joint Conference on Artificial Intelligence (AAAI) 2019
Automating Personnel Rostering by Learning Constraints Using Tensors

Mohit Kumar, Stefano Teso, Patrick De Causmaecker, Luc De Raedt

ICTAI 2019
Toward Faithful Explanatory Active Learning with Self-explainable Neural Nets

Stefano Teso

3rd International Tutorial & Workshop on Interactive Adaptive Learning (IAL2019) at ECML-PKDD 2019
Anomaly Detection for CERN Beam Transfer Installations Using Machine Learning

Thiebout Dewitte, Wannes Meert, Elia Van Wolputte, Pieter Van Trappen

International Conference on Accelerator and Large Experimental Physics Control Systems (ICALEPCS) 2019
Ontology-Mediated Queries over Probabilistic Data via Probabilistic Logic Programming

Timothy Van Bremen, Anton Dries, Jean-Christoph Jung

28th ACM International Conference on Information and Knowledge Management 2019
Transforming Probabilistic Programs into Algebraic Circuits for Inference and Learning

Pedro Miguel Zuidberg Dos Martires, Vincent Derkinderen, Robin Manhaeve, Wannes Meert, Angelika Kimmig, Luc De Raedt

Program Transformations for ML Workshop at NeurIPS 2019 2019
Combining learning and constraints for genome-wide protein annotation

Stefano Teso, Luca Masera, Michelangelo Diligenti, Andrea Passerini

BMC BIOINFORMATICS 2019
Predictive spreadsheet autocompletion with constraints

Samuel Kolb, Stefano Teso, Anton Dries, Luc De Raedt

Machine Learning Journal 2019
Constraint Learning: An Appetizer

Stefano Teso

Reasoning Web - Explainable Artificial Intelligence 2019
SynthLog: A Language for Synthesising Inductive Data Models

Yann Dauxais, Clément Gautrais, Anton Dries, Arcchit Jain, Samuel Kolb, Mohit Kumar, Stefano Teso, Elia Van Wolputte, Gust Verbruggen, Luc De Raedt

International Workshops of ECML PKDD 2019

2018

Automating Personnel Rostering by Learning Constraints Using Tensors

Mohit Kumar, Stefano Teso, Patrick De Causmaecker, Luc De Raedt

DSO Workshop - IJCAI 2018
Constructive Preference Elicitation over Hybrid Combinatorial Spaces

Paolo Dragone, Stefano Teso, Andrea Passerini

The AAAI Conference on Artificial Intelligence 2018
Decomposition Strategies for Constructive Preference Elicitation

Paolo Dragone, Stefano Teso, Andrea Passerini

The AAAI Conference on Artificial Intelligence 2018
Learning Constraints from Examples

Luc De Raedt, Andrea Passerini, Stefano Teso

The AAAI Conference on Artificial Intelligence 2018
MERCS: Multi-Directional Ensembles of Regression and Classification treeS

Elia Van Wolputte, Evgeniya Korneva, Hendrik Blockeel

The AAAI Conference on Artificial Intelligence 2018
Constraint Learning and Dynamic Probabilistic Programming

Luc De Raedt

Dagstuhl Seminar 17351 2018
Towards resource-efficient classifiers for always-on monitoring

Jonas Vlasselaer, Wannes Meert, Marian Verhelst

European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases 2018
Sketched Answer Set Programming

Sergey Paramonov; Christian Bessiere; Anton Dries; Luc De Raedt

30th International Conference on Tools with Artificial Intelligence 2018
Automatically wrangling spreadsheets into machine learning data formats

Gust Verbruggen, Luc De Raedt

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2018
COBRAS: Interactive clustering with pairwise queries

Toon Van Craenendonck, Sebastijan Dumancic, Elia Van Wolputte, Hendrik Blockeel

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2018
Learning SMT(LRA) constraints using SMT solvers

Samuel Kolb, Stefano Teso, Andrea Passerini, Luc De Raedt

IJCAI International Joint Conference on Artificial Intelligence 2018
Pyconstruct: Constraint Programming Meets Structured Prediction

Paolo Dragone, Stefano Teso, Andrea Passerini

IJCAI International Joint Conference on Artificial Intelligence 2018
Elements of an automatic data scientist

Luc De Raedt, Hendrik Blockeel, Samuel Kolb, Stefano Teso, Gust Verbruggen

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2018
Constructive Preference Elicitation

Paolo Dragone, Stefano Teso, Andrea Passerini

Front. Robotics and AI 2018 2018
Hybrid ASP-based Approach to Pattern Mining

Sergey Paramonov, Daria Stepanova, Pauli Miettinen

Theory and Practice of Logic Programming 2018
Automating Data Science (Dagstuhl Seminar 18401)

Tijl De Bie, Luc De Raedt, Holger H. Hoos, Padhraic Smyth

Automating Data Science Seminar 2018

2017

TaCLe: learning constraints in tabular data

Sergey Paramonov, Samuel Kolb, Tias Guns, Luc De Raedt

International Conference on Information and Knowledge Management 2017
Constructive Preference Elicitation for Multiple Users with Setwise Max-margin

Stefano Teso, Andrea Passerini, Paolo Viappiani

International Conference on Algorithmic Decision Theory 2017
Learning constraints in spreadsheets and tabular data

Samuel Kolb, Sergey Paramonov, Tias Guns, Luc De Raedt

Machine Learning 2017
Declarative Data Analysis

Hendrik Blockeel

International Journal of Data Science and Analytics 2017
Towards automated relational data wrangling

Gust Verbruggen, Luc De Raedt

AutoML 2017 @ ECML-PKDD 2017
Learning constraints and formulae for spreadsheets

Luc De Raedt

Approaches and Applications of Inductive Programming Seminar 2017
Generic Mining of Condensed Pattern Representations under Constraints.

Sergey Paramonov, Chen Tao, Tias Guns

Young Scientist's International Workshop on Trends in Information Processing 2017

2016

Towards synthesising inductive data models

Luc De Raedt

Data Science Summit 2016
Can we automate data science?

Luc De Raedt

European Data Science Conference edition:1 2016

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2022

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2016