CUTS-GPR performs numerically exact Gaussian process regression with near-linear scaling in training points N and low-order polynomial scaling in dimensions D by exploiting additive kernels on incomplete grids.
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Quantum algorithm finds eigenvalues of parameterized matrix families by minimizing singular values and applies it to Schrödinger equation collocation with O(sqrt(N)) scaling.
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Don't Get Your Kroneckers in a Twist: Gaussian Processes on High-Dimensional Incomplete Grids
CUTS-GPR performs numerically exact Gaussian process regression with near-linear scaling in training points N and low-order polynomial scaling in dimensions D by exploiting additive kernels on incomplete grids.
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Quantum algorithm for solving generalized eigenvalue problems with application to the Schr\"odinger equation
Quantum algorithm finds eigenvalues of parameterized matrix families by minimizing singular values and applies it to Schrödinger equation collocation with O(sqrt(N)) scaling.