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Empowering approximate Bayesian neural networks with functional priors through anchored ensembling for mechanics surrogate modeling applications
Research article (Computer Methods in Applied Mechanics and Engineering, 2024) · cited 10× · AI/ML
Empowering approximate Bayesian neural networks with functional priors through anchored ensembling for mechanics surrogate modeling applications
Summary
Empowering approximate Bayesian neural networks with functional priors through anchored ensembling for mechanics surrogate modeling applications is a scholarly article[1].
Key Facts
Empowering approximate Bayesian neural networks with functional priors through anchored ensembling for mechanics surrogate modeling applications's instance of is recorded as scholarly article[2].
References
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Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.
APA4ort.xyz Knowledge Graph. (2026). Empowering approximate Bayesian neural networks with functional priors through anchored ensembling for mechanics surrogate modeling applications. Retrieved May 24, 2026, from https://4ort.xyz/entity/empowering-approximate-bayesian-neural-networks-with-functional-priors-through-anchored-ensembling-for-mechanics-surroga
MLA“Empowering approximate Bayesian neural networks with functional priors through anchored ensembling for mechanics surrogate modeling applications.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/empowering-approximate-bayesian-neural-networks-with-functional-priors-through-anchored-ensembling-for-mechanics-surroga.
BibTeX@misc{4ortxyz_empowering-approximate-bayesian-neural-networks-with-functional-priors-through-anchored-ensembling-for-mechanics-surroga_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Empowering approximate Bayesian neural networks with functional priors through anchored ensembling for mechanics surrogate modeling applications}}, year = {2026}, url = {https://4ort.xyz/entity/empowering-approximate-bayesian-neural-networks-with-functional-priors-through-anchored-ensembling-for-mechanics-surroga}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Empowering approximate Bayesian neural networks with functional priors through anchored ensembling for mechanics surrogate modeling applications — https://4ort.xyz/entity/empowering-approximate-bayesian-neural-networks-with-functional-priors-through-anchored-ensembling-for-mechanics-surroga (retrieved 2026-05-24)
