22 citations · 44 across the 14 of their papers we have counts for
3 papers · 1 filter
SurvCF(t): Counterfactual Explanations for Survival Analysis in Predictive Maintenance Multivariate Time Series Data
Zara Karazian, Panagiotis Papapetrou, Sindri Magnússon +2
Predictive maintenance relies on accurate Remaining Useful Life estimation, often formulated using survival analysis over multivariate time-series data. While modern deep survival…
Probabilistic Machine Learning for Uncertainty-Aware Diagnosis of Industrial Systems
Arman Mohammadi, Mattias Krysander, Daniel Jung +1
Deep neural networks has been increasingly applied in fault diagnostics, where it uses historical data to capture systems behavior, bypassing the need for high-fidelity physical mo…
Usage-Specific Survival Modeling Based on Operational Data and Neural Networks
Olov Holmer, Mattias Krysander, Erik Frisk
Accurate predictions of when a component will fail are crucial when planning maintenance, and by modeling the distribution of these failure times, survival models have shown to be…