The primary objective of this collection is to showcase cutting-edge research on explainability techniques and applications of deep learning neural networks, encompassing a spectrum of neural ...

Today, neural networks have already solved the challenges ... Neurosymbolic AI is therefore also related to the notion of explainability. Rather than simply trusting that an algorithmic output ...

Many AI-enabled medtech products leverage machine learning or deep learning. In order to address the opaque decision-making ...

Five common ML models (logistic regression, support vector machine (SVM), neural networks, decision trees (DT), and random forest (RF)) were applied. The proposed explainability methods (HEX-SC ...

This dual focus on performance and explainability is crucial for aviation ... helping to improve flight safety and operational efficiency. Neural Networks: A set of algorithms modeled after ...