3 papers
cs.LG2026
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…
cs.LG2025
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…
eess.SY2024
The LiU-ICE Benchmark -- An Industrial Fault Diagnosis Case Study
Daniel Jung, Erik Frisk, Mattias Krysander
This paper presents the LiU-ICE fault diagnosis benchmark. The purpose of the benchmark is to support fault diagnosis research by providing data and a model of an industrially rele…