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A scalable AI-based approach, SAGIPS, effectively addresses inverse problems by leveraging generative adversarial networks and high-performance computing. Demonstrated on a nuclear physics test case, SAGIPS reduces uncertainties in probabilistic solutions and scales linearly with computational resources, enabling application to larger, more complex scientific problems across various fields.