Do Bayesian Neural Networks Improve Weapon System Predictive Maintenance?

Michael Potter; Miru Jun

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arXiv · 2312.10494

Do Bayesian Neural Networks Improve Weapon System Predictive Maintenance?

Michael Potter·Miru Jun

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Abstract

We implement a Bayesian inference process for Neural Networks to model the time to failure of highly reliable weapon systems with interval-censored data and time-varying covariates. We analyze and benchmark our approach, LaplaceNN, on synthetic and real datasets with standard classification metrics such as Receiver Operating Characteristic (ROC) Area Under Curve (AUC) Precision-Recall (PR) AUC, and reliability curve visualizations.

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Michael Potter, Miru Jun. 2023-12-16. Do Bayesian Neural Networks Improve Weapon System Predictive Maintenance?. https://arxiv.org/abs/2312.10494

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