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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

ArXiv CS.AI1d ago
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This survey examines how to build interpretable surrogate models that reduce computational costs while maintaining explainability in complex system simulations. As AI systems become decision-critical across scientific and engineering domains, understanding model behavior through explainable AI techniques is essential for trustworthy deployment and regulatory compliance.

Black-box simulators need interpretable surrogates to reveal how inputs drive outputs.

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