Neuron Activation Coverage: Rethinking Out-of-distribution Detection and Generalization

arXiv:2306.02879v3 Announce Type: replace
Abstract: The out-of-distribution (OOD) problem generally arises when neural networks encounter data that significantly deviates from the training data distribution, i.e., in-distribution (InD). In this paper, we study the OOD problem from a neuron activation view. We first formulate neuron activation states by considering both the neuron output and its influence on model decisions. Then, to characterize the relationship between neurons and OOD issues, we introduce the \textit{neuron activation coverage} (NAC) -- a simple measure for …

abstract arxiv coverage cs.lg data detection distribution networks neural networks neuron paper study training training data type view