Do Bayesian Neural Networks Improve Weapon System Predictive Maintenance?

• URL: http://arxiv.org/abs/2312.10494v2
• Date: Sat, 6 Jan 2024 13:38:01 GMT
• Title: Do Bayesian Neural Networks Improve Weapon System Predictive Maintenance?
• Abstract summary: We implement a Bayesian inference process for Neural Networks to model the time to failure of highly reliable weapon systems. We analyze and benchmark our approach, LaplaceNN, on synthetic and real datasets.
• Score: 0.9790236766474201
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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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