Informace o publikaci
Gaussian-Based Runtime Detection of Out-of-distribution Inputs for Neural Networks
| Autoři | |
|---|---|
| Rok publikování | 2021 |
| Druh | Článek ve sborníku |
| Konference | Runtime Verification - 21st International Conference, RV 2021, Virtual Event, October 11-14, 2021, Proceedings |
| Fakulta / Pracoviště MU | |
| Citace | |
| Doi | https://doi.org/10.1007/978-3-030-88494-9_14 |
| Popis | In this short paper, we introduce a simple approach for runtime monitoring of deep neural networks and show how to use it for out-of-distribution detection. The approach is based on inferring Gaussian models of some of the neurons and layers. Despite its simplicity, it performs better than recently introduced approaches based on interval abstractions which are traditionally used in verification. |