Neuro-symbolic AI is an emerging subfield of Artificial Intelligence that brings together two
hitherto distinct approaches.” Neuro” refers to the artificial neural networks prominent in …

We introduce DeepProbLog, a probabilistic logic programming language that incorporates
deep learning by means of neural predicates. We show how existing inference and learning …

A multitude of different probabilistic programming languages exists today, all extending a
traditional programming language with primitives to support modeling of complex, structured …

We introduce DeepProbLog, a neural probabilistic logic programming language that
incorporates deep learning by means of neural predicates. We show how existing inference …

Recent advances in neural-symbolic learning, such as DeepProbLog, extend probabilistic
logic programs with neural predicates. Like graphical models, these probabilistic logic …

A fundamental challenge in neuro-symbolic AI is to devise primitives that fuse the logical
and neural concepts. The Neural Theorem Prover has proposed the notion of soft-unification …

Since its birth, the field of Probabilistic Logic Programming has seen a steady increase of
activity, with many proposals for languages and algorithms for inference and learning. This …

The problem of learning logical rules from examples arises in diverse fields, including
program synthesis, logic programming, and machine learning. Existing approaches either …