Luc De Raedt


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Person Info

NAME

Luc

SURNAME

De Raedt

Publications in SciGraph latest 50 shown

  • 2019-12 Representing dynamic biological networks with multi-scale probabilistic models in COMMUNICATIONS BIOLOGY
  • 2018-10-05 Elements of an Automatic Data Scientist in ADVANCES IN INTELLIGENT DATA ANALYSIS XVII
  • 2018-10-05 Automatically Wrangling Spreadsheets into Machine Learning Data Formats in ADVANCES IN INTELLIGENT DATA ANALYSIS XVII
  • 2018-08-23 Semantic and geometric reasoning for robotic grasping: a probabilistic logic approach in AUTONOMOUS ROBOTS
  • 2018-03-15 Relational Affordance Learning for Task-Dependent Robot Grasping in INDUCTIVE LOGIC PROGRAMMING
  • 2018-01 Relational affordances for multiple-object manipulation in AUTONOMOUS ROBOTS
  • 2017-12 kProbLog: an algebraic Prolog for machine learning in MACHINE LEARNING
  • 2017-12 Planning in hybrid relational MDPs in MACHINE LEARNING
  • 2017-12 Relational data factorization in MACHINE LEARNING
  • 2017-10 Learning constraints in spreadsheets and tabular data in MACHINE LEARNING
  • 2017-09 Flexible constrained sampling with guarantees for pattern mining in DATA MINING AND KNOWLEDGE DISCOVERY
  • 2017 Statistical Relational Learning in ENCYCLOPEDIA OF MACHINE LEARNING AND DATA MINING
  • 2017 Multi-relational Data Mining in ENCYCLOPEDIA OF MACHINE LEARNING AND DATA MINING
  • 2016-06 Probabilistic logic programming for hybrid relational domains in MACHINE LEARNING
  • 2016 Inductive Logic Programming in ENCYCLOPEDIA OF MACHINE LEARNING AND DATA MINING
  • 2016 The Inductive Constraint Programming Loop in DATA MINING AND CONSTRAINT PROGRAMMING
  • 2016 Relational Kernel-Based Grasping with Numerical Features in INDUCTIVE LOGIC PROGRAMMING
  • 2016 Modeling in MiningZinc in DATA MINING AND CONSTRAINT PROGRAMMING
  • 2016 kProbLog: An Algebraic Prolog for Kernel Programming in INDUCTIVE LOGIC PROGRAMMING
  • 2016 Learning Constraint Satisfaction Problems: An ILP Perspective in DATA MINING AND CONSTRAINT PROGRAMMING
  • 2016 An Exercise in Declarative Modeling for Relational Query Mining in INDUCTIVE LOGIC PROGRAMMING
  • 2015-07 Probabilistic (logic) programming concepts in MACHINE LEARNING
  • 2015 Rank Matrix Factorisation in ADVANCES IN KNOWLEDGE DISCOVERY AND DATA MINING
  • 2015 Constraint-Based Querying for Bayesian Network Exploration in ADVANCES IN INTELLIGENT DATA ANALYSIS XIV
  • 2015 PageRank, ProPPR, and Stochastic Logic Programs in INDUCTIVE LOGIC PROGRAMMING
  • 2015 ProbLog2: Probabilistic Logic Programming in MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES
  • 2015 Planning in Discrete and Continuous Markov Decision Processes by Probabilistic Programming in MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES
  • 2014 Ranked Tiling in MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES
  • 2014 Lazy and Eager Relational Learning Using Graph-Kernels in STATISTICAL LANGUAGE AND SPEECH PROCESSING
  • 2014 Distributional Clauses Particle Filter in MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES
  • 2013-12 Mining closed patterns in relational, graph and network data in ANNALS OF MATHEMATICS AND ARTIFICIAL INTELLIGENCE
  • 2013 10 Years of Probabilistic Querying – What Next? in ADVANCES IN DATABASES AND INFORMATION SYSTEMS
  • 2013 MCMC Estimation of Conditional Probabilities in Probabilistic Programming Languages in SYMBOLIC AND QUANTITATIVE APPROACHES TO REASONING WITH UNCERTAINTY
  • 2012 Declarative Modeling for Machine Learning and Data Mining in FORMAL CONCEPT ANALYSIS
  • 2012 A Relational Kernel-Based Framework for Hierarchical Image Understanding in STRUCTURAL, SYNTACTIC, AND STATISTICAL PATTERN RECOGNITION
  • 2012 Relational Learning for Spatial Relation Extraction from Natural Language in INDUCTIVE LOGIC PROGRAMMING
  • 2012 Patterns and Logic for Reasoning with Networks in BISOCIATIVE KNOWLEDGE DISCOVERY
  • 2012-01 ILP turns 20 in MACHINE LEARNING
  • 2012 BiQL: A Query Language for Analyzing Information Networks in BISOCIATIVE KNOWLEDGE DISCOVERY
  • 2012 Kernel-Based Logical and Relational Learning with kLog for Hedge Cue Detection in INDUCTIVE LOGIC PROGRAMMING
  • 2012 Declarative Modeling for Machine Learning and Data Mining in ALGORITHMIC LEARNING THEORY
  • 2012 Declarative Modeling for Machine Learning and Data Mining in MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES
  • 2012 Declarative Modeling for Machine Learning and Data Mining in DISCOVERY SCIENCE
  • 2011-05 Guest editorial to the special issue on inductive logic programming, mining and learning in graphs and statistical relational learning in MACHINE LEARNING
  • 2011-05 Effective feature construction by maximum common subgraph sampling in MACHINE LEARNING
  • 2011-02 Stochastic relational processes: Efficient inference and applications in MACHINE LEARNING
  • 2011 Iterative Classification in ENCYCLOPEDIA OF MACHINE LEARNING
  • 2011 In-Sample Evaluation in ENCYCLOPEDIA OF MACHINE LEARNING
  • 2011 Intelligent Backtracking in ENCYCLOPEDIA OF MACHINE LEARNING
  • 2011 Inequalities in ENCYCLOPEDIA OF MACHINE LEARNING
  • Affiliations

  • KU Leuven (current)
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