Abstract Deep learning models have been successful in many areas, but understanding their behavior remains a challenge. Most prior explainable AI ...

Artificial intelligence is changing how we predict river flow—but a new study led by researchers at the University of British ...

Overview: Interpretability tools make machine learning models more transparent by displaying how each feature influences ...

As digital ecosystems expand across industries, so does the threat surface they expose. For Dr. Karthik Kambhampati, a ...

ESG indices in emerging markets often lack long, transparent historical records, making them difficult to analyze with ...

Explainable AI plays a central role in validating model behavior. Using established explainability techniques, the study examines which financial variables drive fraud predictions. The results show a ...

Abstract: This work presents an explainable deep learning for turbulence modelling feature discovery in several flow configurations where conventional approaches perform poorly. The proposed neural ...

ABSTRACT: The advancement of deepfake technologies, leveraging sophisticated artificial intelligence methods, poses substantial cybersecurity risks including misinformation dissemination, identity ...

Abstract: Deep learning (DL) has been widely applied to enhance automatic modulation classification (AMC). However, the elaborate AMC neural networks are susceptible to various adversarial attacks, ...