1 citations · 1 across the 4 of their papers we have counts for
4 papers
Failure Detection in Chemical Processes Using Symbolic Machine Learning: A Case Study on Ethylene Oxidation
Julien Amblard, Niklas Groll, Matthew Tait +3
Over the past decade, Artificial Intelligence has significantly advanced, mostly driven by large-scale neural approaches. However, in the chemical process industry, where safety is…
LearnAD: Learning Interpretable Rules for Brain Networks in Alzheimer's Disease Classification
Thomas Andrews, Mark Law, Sara Ahmadi-Abhari +1
We introduce LearnAD, a neuro-symbolic method for predicting Alzheimer's disease from brain magnetic resonance imaging data, learning fully interpretable rules. LearnAD applies sta…
The Role of Foundation Models in Neuro-Symbolic Learning and Reasoning
Daniel Cunnington, Mark Law, Jorge Lobo +1
Neuro-Symbolic AI (NeSy) holds promise to ensure the safe deployment of AI systems, as interpretable symbolic techniques provide formal behaviour guarantees. The challenge is how t…
A Unifying Framework for Learning Argumentation Semantics
Zlatina Mileva, Antonis Bikakis, Fabio Aurelio D'Asaro +2
Argumentation is a very active research field of Artificial Intelligence concerned with the representation and evaluation of arguments used in dialogues between humans and/or artif…