31 citations · 39 across the 6 of their papers we have counts for
3 papers · 1 filter
Building Trustworthy AI: Transparent AI Systems via Large Language Models, Ontologies, and Logical Reasoning (TranspNet)
Fadi Al Machot, Martin Thomas Horsch, Habib Ullah
Growing concerns over the lack of transparency in AI, particularly in high-stakes fields like healthcare and finance, drive the need for explainable and trustworthy systems. While…
Symbolic-AI-Fusion Deep Learning (SAIF-DL): Encoding Knowledge into Training with Answer Set Programming Loss Penalties by a Novel Loss Function Approach
Fadi Al Machot, Martin Thomas Horsch, Habib Ullah
This paper presents a hybrid methodology that enhances the training process of deep learning (DL) models by embedding domain expert knowledge using ontologies and answer set progra…
Scope of physics-based simulation artefacts
Martin Thomas Horsch, Fadi Al Machot, Jadran Vrabec
Data and metadata documentation requirements for explainable-AI-ready (XAIR) models and data in physics-based simulation technology are discussed by analysing different perspective…