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cs.LG2025★ 2 cited
Global Sensitivity Analysis for Engineering Design Based on Individual Conditional Expectations
Pramudita Satria Palar, Paul Saves, Rommel G. Regis +4
Explainable machine learning techniques have gained increasing attention in engineering applications, especially in aerospace design and analysis, where understanding how input var…
cs.LG2025
SMT-EX: An Explainable Surrogate Modeling Toolbox for Mixed-Variables Design Exploration
Mohammad Daffa Robani, Paul Saves, Pramudita Satria Palar +2
Surrogate models are of high interest for many engineering applications, serving as cheap-to-evaluate time-efficient approximations of black-box functions to help engineers and pra…