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.
Identifying Challenges towards Practical Quantum Advantage through Resource Estimation: The Measurement Roadblock in the Variational Quantum Eigensolver , shorttitle =
2 Pith papers cite this work. Polarity classification is still indexing.
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Benchmarks of separable pair approximation states in orbital-optimized VQE demonstrate consistent approximations for hydrogen chains, alkanes, and small molecules with classical complexity comparable to Hartree-Fock.
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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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Consistent Initial States with Constant Circuit Depth for Quantum Computational Chemistry
Benchmarks of separable pair approximation states in orbital-optimized VQE demonstrate consistent approximations for hydrogen chains, alkanes, and small molecules with classical complexity comparable to Hartree-Fock.