6 citations · 10 across the 5 of their papers we have counts for
5 papers
From Latent Biomarkers to Clinical Rules: Embedding-Guided Rule Mining and Attribution-Based Translation for Interpretable Tabular Learning
Majid Lotfian Delouee, Hamed Ayoobi, Sjors G. J. G. In 't Veld +1
Clinical decision support tools are most useful when accurate predictions are accompanied by understandable explanations. Rule-based models provide transparency, but rules derived…
Argumentative Debates for Transparent Bias Detection [Technical Report]
Hamed Ayoobi, Nico Potyka, Anna Rapberger +1
As the use of AI in society grows, addressing emerging biases is essential to prevent systematic discrimination. Several bias detection methods have been proposed, but, with few ex…
Contestable AI needs Computational Argumentation
Francesco Leofante, Hamed Ayoobi, Adam Dejl +10
AI has become pervasive in recent years, but state-of-the-art approaches predominantly neglect the need for AI systems to be contestable. Instead, contestability is advocated by AI…
ProtoArgNet: Interpretable Image Classification with Super-Prototypes and Argumentation [Technical Report]
Hamed Ayoobi, Nico Potyka, Francesca Toni
We propose ProtoArgNet, a novel interpretable deep neural architecture for image classification in the spirit of prototypical-part-learning as found, e.g., in ProtoPNet. While earl…
Hidden Conflicts in Neural Networks and Their Implications for Explainability
Adam Dejl, Dekai Zhang, Hamed Ayoobi +2
Artificial Neural Networks (ANNs) often represent conflicts between features, arising naturally during training as the network learns to integrate diverse and potentially disagreei…