Explicit block encoding of the DoG operator achieves constant subnormalization factor λ=2 and a closed-form success probability that scales as O(h^4) on fine grids.
Sparse grids.Acta numerica, 13:147–269
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
citation-role summary
background 1
citation-polarity summary
years
2026 2verdicts
UNVERDICTED 2roles
background 1polarities
background 1representative citing papers
Directional Chebyshev harmonics enable spectral path regression for tabular data with closed-form training, competitive accuracy, and explicit interpretability.
citing papers explorer
-
Explicit Block Encoding of Difference-of-Gaussian Operators on a Periodic Grid
Explicit block encoding of the DoG operator achieves constant subnormalization factor λ=2 and a closed-form success probability that scales as O(h^4) on fine grids.
-
Spectral Path Regression: Directional Chebyshev Harmonics for Interpretable Tabular Learning
Directional Chebyshev harmonics enable spectral path regression for tabular data with closed-form training, competitive accuracy, and explicit interpretability.