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Assessing Gaussian Process Regression and Permutationally Invariant Polynomial Approaches To Represent High-Dimensional Potential Energy Surfaces
Research article (Journal of Chemical Theory and Computation, 2018) · cited 104× · AI/ML
Assessing Gaussian Process Regression and Permutationally Invariant Polynomial Approaches To Represent High-Dimensional Potential Energy Surfaces
Summary
Assessing Gaussian Process Regression and Permutationally Invariant Polynomial Approaches To Represent High-Dimensional Potential Energy Surfaces is a scholarly article[1].
Key Facts
Assessing Gaussian Process Regression and Permutationally Invariant Polynomial Approaches To Represent High-Dimensional Potential Energy Surfaces's instance of is recorded as scholarly article[2].
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APA4ort.xyz Knowledge Graph. (2026). Assessing Gaussian Process Regression and Permutationally Invariant Polynomial Approaches To Represent High-Dimensional Potential Energy Surfaces. Retrieved May 24, 2026, from https://4ort.xyz/entity/assessing-gaussian-process-regression-and-permutationally-invariant-polynomial-approaches-to-represent-high-dimensional-
MLA“Assessing Gaussian Process Regression and Permutationally Invariant Polynomial Approaches To Represent High-Dimensional Potential Energy Surfaces.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/assessing-gaussian-process-regression-and-permutationally-invariant-polynomial-approaches-to-represent-high-dimensional-.
BibTeX@misc{4ortxyz_assessing-gaussian-process-regression-and-permutationally-invariant-polynomial-approaches-to-represent-high-dimensional-_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Assessing Gaussian Process Regression and Permutationally Invariant Polynomial Approaches To Represent High-Dimensional Potential Energy Surfaces}}, year = {2026}, url = {https://4ort.xyz/entity/assessing-gaussian-process-regression-and-permutationally-invariant-polynomial-approaches-to-represent-high-dimensional-}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Assessing Gaussian Process Regression and Permutationally Invariant Polynomial Approaches To Represent High-Dimensional Potential Energy Surfaces — https://4ort.xyz/entity/assessing-gaussian-process-regression-and-permutationally-invariant-polynomial-approaches-to-represent-high-dimensional- (retrieved 2026-05-24)
