Survey paper examining interpretable and explainable surrogate modeling approaches for simulation-based systems. Focuses on techniques that enhance transparency and decision-making in metamodeling contexts where simulation approximations are used.
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Interpretable and Explainable Surrogate Modeling for Simulations: A State-of-the-Art Survey and Perspectives on Explainable AI for Decision-Making
Survey of interpretable surrogate modeling techniques that prioritize explainability and transparency for decision-making in simulation approximations—bridging the gap between model accuracy and human comprehensibility.
Friday, April 17, 2026 12:00 PM UTC2 MIN READSOURCE: arXiv CS.AIBY sys://pipeline
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