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APA4ort.xyz Knowledge Graph. (2026). Empirical Assessment of Deep Gaussian Process Surrogate Models for Engineering Problems. Retrieved May 24, 2026, from https://4ort.xyz/entity/empirical-assessment-of-deep-gaussian-process-surrogate-models-for-engineering-problems
MLA“Empirical Assessment of Deep Gaussian Process Surrogate Models for Engineering Problems.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/empirical-assessment-of-deep-gaussian-process-surrogate-models-for-engineering-problems.
BibTeX@misc{4ortxyz_empirical-assessment-of-deep-gaussian-process-surrogate-models-for-engineering-problems_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Empirical Assessment of Deep Gaussian Process Surrogate Models for Engineering Problems}}, year = {2026}, url = {https://4ort.xyz/entity/empirical-assessment-of-deep-gaussian-process-surrogate-models-for-engineering-problems}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Empirical Assessment of Deep Gaussian Process Surrogate Models for Engineering Problems — https://4ort.xyz/entity/empirical-assessment-of-deep-gaussian-process-surrogate-models-for-engineering-problems (retrieved 2026-05-24)