Corey M. Bryant

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In this work, we investigate adaptive approaches to control errors in numerical approximations of differential equations with uncertain or random data and coefficients. The adaptivity is based on a posteriori error estimation and the approach relies on the ability to decompose the a posteriori error estimate into contributions from the physical(More)
—The decision to incorporate cross-validation into validation processes of mathematical models raises an immediate question – how should one partition the data into calibration and validation sets? We answer this question systematically: we present an algorithm to find the optimal partition of the data subject to certain constraints. While doing this, we(More)
Acquired uniparental disomy (aUPD) is a common finding in myeloid malignancies and typically acts to convert a somatically acquired heterozygous mutation to homozygosity. We sought to identify the target of chromosome 14 aUPD (aUPD14), a recurrent abnormality in myeloid neoplasms and population cohorts of elderly individuals. We identified 29 cases with(More)
Parameter estimation for complex models using Bayesian inference is usually a very costly process as it requires a large number of solves of the forward problem. We propose here an approach to reduce the computational cost by constructing surrogate models that provide approximations of the true solutions of the forward problem. The surrogate models are(More)
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