most citedIntegrating supervised and unsupervised learning approaches to unveil critical process inputs

8 citations · 8 across the 5 of their papers we have counts for

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stat.OT2025

Data-driven inverse uncertainty quantification: application to the Chemical Vapor Deposition Reactor Modeling

Geremy Loachamín, Eleni D. Koronaki, Dimitrios G. Giovanis +4

This study presents a Bayesian framework for (inverse) uncertainty quantification and parameter estimation in a two-step Chemical Vapor Deposition coating process using production…