Luc De Raedt

DeepProofLog: Efficient Proving in Deep Stochastic Logic Programs AAAI 2026 NeSyA: Neurosymbolic Automata IJCAI 2025 Neurosymbolic Reinforcement Learning: Playing MiniHack with Probabilistic Logic Shields AAAI 2025 Relational Neurosymbolic Markov Models AAAI 2025 The Gradient of Algebraic Model Counting AAAI 2025 CLEVR-POC: Reasoning-Intensive Visual Question Answering in Partially Observable Environments COLING 2024 Inference and Learning in Dynamic Decision Networks Using Knowledge Compilation AAAI 2024 On the Hardness of Probabilistic Neurosymbolic Learning ICML 2024 SayCanPay: Heuristic Planning with Large Language Models Using Learnable Domain Knowledge AAAI 2024 Neural probabilistic logic programming in discrete-continuous domains UAI 2023 Safe Reinforcement Learning via Probabilistic Logic Shields IJCAI 2023 Soft-Unification in Deep Probabilistic Logic NeurIPS 2023 DeepStochLog: Neural Stochastic Logic Programming AAAI 2022 Inference and Learning with Model Uncertainty in Probabilistic Logic Programs AAAI 2022 Democratizing Constraint Satisfaction Problems through Machine Learning AAAI 2021 Learning CNF Theories Using MDL and Predicate Invention IJCAI 2021 Mapping probability word problems to executable representations EMNLP 2021 From Statistical Relational to Neuro-Symbolic Artificial Intelligence IJCAI 2020 Learning MAX-SAT from Contextual Examples for Combinatorial Optimisation AAAI 2020 ProbAnch: a Modular Probabilistic Anchoring Framework IJCAI 2020 Acquiring Integer Programs from Data IJCAI 2019 Exact and Approximate Weighted Model Integration with Probability Density Functions Using Knowledge Compilation AAAI 2019 How to Exploit Structure while Solving Weighted Model Integration Problems UAI 2019 Learning from Implicit Information in Natural Language Instructions for Robotic Manipulations NAACL 2019 The pywmi Framework and Toolbox for Probabilistic Inference using Weighted Model Integration IJCAI 2019 DeepProbLog: Neural Probabilistic Logic Programming NeurIPS 2018 Learning SMT(LRA) Constraints using SMT Solvers IJCAI 2018 Solving Probability Problems in Natural Language IJCAI 2017 Stochastic Constraint Programming with And-Or Branch-and-Bound IJCAI 2017 Anytime Inference in Probabilistic Logic Programs with Tp-Compilation IJCAI 2015 Graph Invariant Kernels IJCAI 2015 Inducing Probabilistic Relational Rules from Probabilistic Examples IJCAI 2015 kLog: A Language for Logical and Relational Learning with Kernels (Extended Abstract) IJCAI 2015 kLogNLP: Graph Kernel–based Relational Learning of Natural Language ACL 2014 Allocentric Pose Estimation ICCV 2013 MiningZinc: A Modeling Language for Constraint-based Mining IJCAI 2013 A Statistical Relational Learning Approach to Identifying Evidence Based Medicine Categories EMNLP 2012 Integrating Naïve Bayes and FOIL JMLR 2007 Kernels on Prolog Proof Trees: Statistical Learning in the ILP Setting JMLR 2006