Abstract: One embodiment provides a method and a system for diagnosing faults in a physical system. During operation, the system can create a fault-augmented model of the physical system by considering various potential faults, and it can generate a machine-learning model to predict an operation mode of the physical system using the outputs of the physical system. A respective operation mode corresponds to normal operation or a potential fault in the physical system. The system can generate a plurality of training samples based on the fault-augmented model, use the training samples to train the machine-learning model to learn a sequence of inputs and model parameters that minimizes an uncertainty of the predicted operation mode, and then apply the learned sequence of inputs and the trained machine-learning model on the physical system to determine the operation mode of the physical system.