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theoretical advances into practical insight and tools that can support analysis, design and decision-making for AI-enabled space systems, thereby bridging the emerging scientific theory of deep learning with
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-driven dynamical systems, perturbative theories in celestial mechanics, symbolic regression, inverse methodologies via differentiable simulations, efficient high-dimensional numerical quadrature and more
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