← Authors

Luc De Raedt

40 papers · 2006–2026 · 12 conferences · across top CS/AI conferences

Achievements

🐣 Hot Topic Early Bird πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (10) 🧭 Keyword Pioneer 🌍 Conference Polyglot (12) πŸƒ Academic Marathon (19) 🐝 Cross-Pollinator (15) 🌈 Renaissance Researcher (9) 🧬 Topic Evolution πŸ† Keyword Champion (4) πŸ“ˆ Trend Setter πŸ”₯ Unstoppable (9) πŸ—ƒοΈ Keyword Collector (145) ⚑ Prolific Year (5) πŸ’Ž Century Club (39) πŸš€ Conference Pioneer

Conferences

IJCAI (15) AAAI (11) EMNLP (2) JMLR (2) NIPS (2) UAI (2) ACL (1) COLING (1) CONLL (1) ICCV (1) ICML (1) NAACL (1)

Top co-authors

Pedro Zuidberg Dos Martires (9) Giuseppe Marra (7) Paolo Frasconi (6) Angelika Kimmig (6) Samuel Kolb (5) Mathias Verbeke (4) Robin Manhaeve (4) Anton Dries (4) Walter Daelemans (3) Stefano Teso (3)

Keywords

neurosymbolic ai (4) constraint learning (4) probabilistic logic (4) bayesian inference (3) probabilistic inference (3) knowledge compilation (3) probabilistic logic programming (3) weighted model integration (3) inductive logic programming (2) reinforcement learning (2) weighted model counting (2) probabilistic programming (2) relational learning (2) machine learning (2) symbolic reasoning (2) combinatorial optimization (2) markov decision process (2) constraint satisfaction (2) logical reasoning (2) probabilistic reasoning (2)

Papers

DeepProofLog: Efficient Proving in Deep Stochastic Logic Programs AAAI 2026
NeSyA: Neurosymbolic Automata IJCAI 2025
Relational Neurosymbolic Markov Models AAAI 2025
The Gradient of Algebraic Model Counting AAAI 2025
Neurosymbolic Reinforcement Learning: Playing MiniHack with Probabilistic Logic Shields AAAI 2025
CLEVR-POC: Reasoning-Intensive Visual Question Answering in Partially Observable Environments COLING 2024
On the Hardness of Probabilistic Neurosymbolic Learning ICML 2024
SayCanPay: Heuristic Planning with Large Language Models Using Learnable Domain Knowledge AAAI 2024
Inference and Learning in Dynamic Decision Networks Using Knowledge Compilation AAAI 2024
Neural probabilistic logic programming in discrete-continuous domains UAI 2023
Soft-Unification in Deep Probabilistic Logic NIPS 2023
Safe Reinforcement Learning via Probabilistic Logic Shields IJCAI 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
ProbAnch: a Modular Probabilistic Anchoring Framework IJCAI 2020
From Statistical Relational to Neuro-Symbolic Artificial Intelligence IJCAI 2020
Learning MAX-SAT from Contextual Examples for Combinatorial Optimisation AAAI 2020
The pywmi Framework and Toolbox for Probabilistic Inference using Weighted Model Integration 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
Acquiring Integer Programs from Data IJCAI 2019
DeepProbLog: Neural Probabilistic Logic Programming NIPS 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
kLog: A Language for Logical and Relational Learning with Kernels (Extended Abstract) IJCAI 2015
Graph Invariant Kernels IJCAI 2015
Anytime Inference in Probabilistic Logic Programs with Tp-Compilation IJCAI 2015
Inducing Probabilistic Relational Rules from Probabilistic Examples 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
A Statistical Relational Learning Approach to Identifying Evidence Based Medicine Categories CONLL 2012
Integrating Naïve Bayes and FOIL JMLR 2007
Kernels on Prolog Proof Trees: Statistical Learning in the ILP Setting JMLR 2006