Deep Neural Networks (DNNs) are extensively deployed in today’s safety-critical autonomous systems thanks to their excellent performance. However, they known make mistakes unpredictably, e.g., a DNN may misclassify an object if it is used for perception, or issue unsafe control commands planning and control. One common cause such unpredictable Out-of-Distribution (OOD) input samples, i.e., samp...