Black-Box Optimization with Local Generative Surrogates
Black-Box Optimization with Local Generative Surrogates
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Ithaca: Cornell University Library, arXiv.org
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English
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Ithaca: Cornell University Library, arXiv.org
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We propose a novel method for gradient-based optimization of black-box simulators using differentiable local surrogate models. In fields such as physics and engineering, many processes are modeled with non-differentiable simulators with intractable likelihoods. Optimization of these forward models is particularly challenging, especially when the si...
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Black-Box Optimization with Local Generative Surrogates
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TN_cdi_proquest_journals_2354571941
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2354571941
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2331-8422