11 citations · 36 across the 18 of their papers we have counts for
4 papers · 1 filter
XAI-Units: Benchmarking Explainability Methods with Unit Tests
Jun Rui Lee, Sadegh Emami, Michael David Hollins +5
Feature attribution (FA) methods are widely used in explainable AI (XAI) to help users understand how the inputs of a machine learning model contribute to its outputs. However, dif…
A Knowledge Distillation Approach for Sepsis Outcome Prediction from Multivariate Clinical Time Series
Anna Wong, Shu Ge, Nassim Oufattole +4
Sepsis is a life-threatening condition triggered by an extreme infection response. Our objective is to forecast sepsis patient outcomes using their medical history and treatments,…
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…
Treatment-RSPN: Recurrent Sum-Product Networks for Sequential Treatment Regimes
Adam Dejl, Harsh Deep, Jonathan Fei +2
Sum-product networks (SPNs) have recently emerged as a novel deep learning architecture enabling highly efficient probabilistic inference. Since their introduction, SPNs have been…