Despite its great success, machine learning can have its limits when dealing with insufficient
training data. A potential solution is the additional integration of prior knowledge into the …

Artificial Intelligence (AI)‐based systems are widely employed nowadays to make decisions
that have far‐reaching impact on individuals and society. Their decisions might affect …

Abstract Current advances in Artificial Intelligence (AI) and Machine Learning have achieved
unprecedented impact across research communities and industry. Nevertheless, concerns …

Recent research in artificial intelligence and machine learning has largely emphasized
general-purpose learning and ever-larger training sets and more and more compute. In …

Graphs arise naturally in many real-world applications including social networks,
recommender systems, ontologies, biology, and computational finance. Traditionally …

Abstract Knowledge graphs contain knowledge about the world and provide a structured
representation of this knowledge. Current knowledge graphs contain only a small subset of …

Abstract Knowledge graphs (KGs) typically contain temporal facts indicating relationships
among entities at different times. Due to their incompleteness, several approaches have …

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

Artificial Neural Networks are powerful function approximators capable of modelling
solutions to a wide variety of problems, both supervised and unsupervised. As their size and …

The study and understanding of human behaviour is relevant to computer science, artificial
intelligence, neural computation, cognitive science, philosophy, psychology, and several …