Monitor and Recover: a Paradigm for Future Research on Distribution Shift in Learning-Enabled Cyber-Physical Systems

With the known vulnerability of neural networks to distribution shift, maintaining reliability in learning-enabled cyber-physical systems poses a salient challenge. In response, many existing methods adopt a detect and abstain methodology, aiming to detect distribution shift at inference time so...