Introduction Autonomous systems with learning-enabled components (LECs) rely on deep neural networks in order to achieve high performance for various applications. It is well known that neural networks are vulnerable to distribution shifts (e.g., weather changes and adversarial perturbations). This vulnerability raises the safety and robustness concerns of learning-enabled cyber-physical systems (CPS) in the real world. For instance, in an…