Variational Autoencoder for Classification and Regression for Out-of-Distribution Detection in Learning-Enabled Cyber-Physical Systems
Learning-Enabled Components (LECs), such as neural networks, are broadly employed in Cyber-Physical Systems (CPSs) to tackle a wide variety of complex tasks in high-uncertainty environments. However, the training dataset is inevitably incomplete, and Out-Of-Distribution (OOD) data not encountered du...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2022-12-01
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| Series: | Applied Artificial Intelligence |
| Online Access: | http://dx.doi.org/10.1080/08839514.2022.2131056 |