Vortrag von: Philippe Crackau
Titel: Examining Image Classifier Decisions Through the Lense of Probabilistic Relational Explanations – Extending the CoReX Framework by Probabilistic Logic Programming
Zeit: 11.06.2025 - 13:00 - 14:00
Ort: WE5/05.013 und Teams
Abstract:
Explainability and human interpretability are relevant topics of research due to
the ubiquity of AI systems in various fields through the rise of Deep Neural Net-
works and the growing awareness of their shortcomings. The CoReX-framework
is one such system, which uses Prolog to learn human readable First-order logic
rules from features informing the NNs decision-making.
In this thesis, the current Prolog-explainer Aleph will be replaced with a prob-
abilistic inductive logic programming extension in Prolog by Riguzzi et al. in
order to gain an additional layer of information by weighting the certainty of
the classification.
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