Introduces Δ-VFE pivoted Cholesky, a pivot rule maximizing the one-step gain in a VFE functional for kernel matrices via closed-form decomposition and batch sampling, yielding improved GP objective values and accuracy at low ranks.
On the Low-Rank Approximation by the Pivoted
3 Pith papers cite this work. Polarity classification is still indexing.
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A reorganized Hartree-Fock framework imposes tunable orbital locality by pairing local degrees of freedom with local solution conditions, maintaining efficient SCF optimization and competitive reaction-energy accuracy.
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.
citing papers explorer
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Variational Free Energy Pivot Selection for Pivoted Cholesky
Introduces Δ-VFE pivoted Cholesky, a pivot rule maximizing the one-step gain in a VFE functional for kernel matrices via closed-form decomposition and batch sampling, yielding improved GP objective values and accuracy at low ranks.
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Approximating Hartree-Fock theory via an efficiently local reformulation
A reorganized Hartree-Fock framework imposes tunable orbital locality by pairing local degrees of freedom with local solution conditions, maintaining efficient SCF optimization and competitive reaction-energy accuracy.
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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.