3 papers
cs.LG2023
Towards Rigorous Design of OoD Detectors
Chih-Hong Cheng, Changshun Wu, Harald Ruess +1
Out-of-distribution (OoD) detection techniques are instrumental for safety-related neural networks. We are arguing, however, that current performance-oriented OoD detection techniq…
cs.SE2022
Prioritizing Corners in OoD Detectors via Symbolic String Manipulation
Chih-Hong Cheng, Changshun Wu, Emmanouil Seferis +1
For safety assurance of deep neural networks (DNNs), out-of-distribution (OoD) monitoring techniques are essential as they filter spurious input that is distant from the training d…
cs.LG2021
Customizable Reference Runtime Monitoring of Neural Networks using Resolution Boxes
Changshun Wu, Yliès Falcone, Saddek Bensalem
Classification neural networks fail to detect inputs that do not fall inside the classes they have been trained for. Runtime monitoring techniques on the neuron activation pattern…