Gaussian Moments as Physically Inspired Molecular Descriptors for Accurate and Scalable Machine Learning Potentials
Summary
Gaussian Moments as Physically Inspired Molecular Descriptors for Accurate and Scalable Machine Learning Potentials is a scholarly article[1].
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Gaussian Moments as Physically Inspired Molecular Descriptors for Accurate and Scalable Machine Learning Potentials's instance of is recorded as scholarly article[2].
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APA4ort.xyz Knowledge Graph. (2026). Gaussian Moments as Physically Inspired Molecular Descriptors for Accurate and Scalable Machine Learning Potentials. Retrieved May 24, 2026, from https://4ort.xyz/entity/gaussian-moments-as-physically-inspired-molecular-descriptors-for-accurate-and-scalable-machine-learning-potentials
MLA“Gaussian Moments as Physically Inspired Molecular Descriptors for Accurate and Scalable Machine Learning Potentials.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/gaussian-moments-as-physically-inspired-molecular-descriptors-for-accurate-and-scalable-machine-learning-potentials.
BibTeX@misc{4ortxyz_gaussian-moments-as-physically-inspired-molecular-descriptors-for-accurate-and-scalable-machine-learning-potentials_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Gaussian Moments as Physically Inspired Molecular Descriptors for Accurate and Scalable Machine Learning Potentials}}, year = {2026}, url = {https://4ort.xyz/entity/gaussian-moments-as-physically-inspired-molecular-descriptors-for-accurate-and-scalable-machine-learning-potentials}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Gaussian Moments as Physically Inspired Molecular Descriptors for Accurate and Scalable Machine Learning Potentials — https://4ort.xyz/entity/gaussian-moments-as-physically-inspired-molecular-descriptors-for-accurate-and-scalable-machine-learning-potentials (retrieved 2026-05-24)
