3 papers
stat.ME2025
Uncertainty calibration for latent-variable regression models
Zina-Sabrina Duma, Otto Lamminpää, Jouni Susiluoto +6
Uncertainty quantification is essential for scientific analysis, as it allows for the evaluation and interpretation of variability and reliability in complex systems and datasets.…
cs.CE2025
Optimising Kernel-based Multivariate Statistical Process Control
Zina-Sabrina Duma, Victoria Jorry, Tuomas Sihvonen +2
Multivariate Statistical Process Control (MSPC) is a framework for monitoring and diagnosing complex processes by analysing the relationships between multiple process variables sim…
cs.LG2024
Kernel-based retrieval models for hyperspectral image data optimized with Kernel Flows
Zina-Sabrina Duma, Tuomas Sihvonen, Jouni Susiluoto +3
Kernel-based statistical methods are efficient, but their performance depends heavily on the selection of kernel parameters. In literature, the optimization studies on kernel-based…