Mitigating Overconfidence in Out-of-Distribution Detection by Capturing Extreme Activations

Mohammad Azizmalayeri, Ameen Abu-Hanna, Giovanni Cinà

Detecting out-of-distribution (OOD) instances is crucial for the reliable deployment of machine learning models in real-world scenarios. OOD inputs are commonly expected to cause a…