Researchers have developed new error estimates for approximating functions using Hermite expansions combined with adaptive coordinate transformations. Their analysis demonstrates an equivalence principle where approximating a function in a transformed basis is akin to approximating its pullback in the Hermite basis. This theoretical framework, which leverages classical approximation theory, provides insights into the convergence of adaptive Hermite approximations, particularly those utilizing normalizing flows as seen in computational quantum physics. AI
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RANK_REASON Academic paper on theoretical convergence properties of approximation methods.
