Clint Scovel

Clint ScovelClint Scovel is a Research Associate in the Computing and Mathematical Sciences department at the California Institute of Technology, after a twenty-six-year career at Los Alamos National Laboratory, including foundational research in symplectic algoithms and machine learning. He received his Ph.D. in mathematics from the Courant Institute of Mathematics at New York University in 1983. He currently works on uncertainty quantification, Bayesian methods, incorporating computational complexity in Wald's statistical decision theory, operator adapted wavelets and fast solvers. Read More Read Less

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Kernel Mode Decomposition and the Programming of Kernels38 %
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Operator-Adapted Wavelets, Fast Solvers, and Numerical Homogenization7 % NR
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