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https://doi.org/10.1007/978-3-658-39909-2o improve the solution of such inverse problems. In applications where prior training data are available, sparse manifold learning methods can be adopted to tailor parameter representations to the specific requirements of the prior data. However, a major risk in employing prior training data is the