activity
20102023
most citedNew Liftable Classes for First-Order Probabilistic Inference

19 citations · 30 across the 5 of their papers we have counts for

collaborators

5 papers

cs.AI20231 cited

smProbLog: Stable Model Semantics in ProbLog for Probabilistic Argumentation

Pietro Totis, Angelika Kimmig, Luc De Raedt

Argumentation problems are concerned with determining the acceptability of a set of arguments from their relational structure. When the available information is uncertain, probabil…

cs.AI20238 cited

Neural Probabilistic Logic Programming in Discrete-Continuous Domains

Lennert De Smet, Pedro Zuidberg Dos Martires, Robin Manhaeve +3

Neural-symbolic AI (NeSy) allows neural networks to exploit symbolic background knowledge in the form of logic. It has been shown to aid learning in the limited data regime and to…

cs.LO2020

Proceedings 36th International Conference on Logic Programming (Technical Communications)

Francesco Ricca, Alessandra Russo, Sergio Greco +9

Since the first conference held in Marseille in 1982, ICLP has been the premier international event for presenting research in logic programming. Contributions are solicited in all…

cs.AI201619 cited

New Liftable Classes for First-Order Probabilistic Inference

Seyed Mehran Kazemi, Angelika Kimmig, Guy Van den Broeck +1

Statistical relational models provide compact encodings of probabilistic dependencies in relational domains, but result in highly intractable graphical models. The goal of lifted i…

cs.LO20102 cited

DNF Sampling for ProbLog Inference

Dimitar Sht. Shterionov, Angelika Kimmig, Theofrastos Mantadelis +1

Inference in probabilistic logic languages such as ProbLog, an extension of Prolog with probabilistic facts, is often based on a reduction to a propositional formula in DNF. Calcul…