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Efficient Bayesian inference using adversarial machine learning and low-complexity surrogate models

Research article (Computers & Chemical Engineering, 2021) · cited 14× · AI/ML
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Efficient Bayesian inference using adversarial machine learning and low-complexity surrogate models

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Efficient Bayesian inference using adversarial machine learning and low-complexity surrogate models is a scholarly article[1].

Key Facts

  • Efficient Bayesian inference using adversarial machine learning and low-complexity surrogate models's instance of is recorded as scholarly article[2].

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Direct Wikidata claims

  1. [2] ↑ . wikidata.org.

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  1. [1] ↑ . Wikidata. wikidata.org.

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APA 4ort.xyz Knowledge Graph. (2026). Efficient Bayesian inference using adversarial machine learning and low-complexity surrogate models. Retrieved May 24, 2026, from https://4ort.xyz/entity/efficient-bayesian-inference-using-adversarial-machine-learning-and-low-complexity-surrogate-models
MLA “Efficient Bayesian inference using adversarial machine learning and low-complexity surrogate models.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/efficient-bayesian-inference-using-adversarial-machine-learning-and-low-complexity-surrogate-models.
BibTeX @misc{4ortxyz_efficient-bayesian-inference-using-adversarial-machine-learning-and-low-complexity-surrogate-models_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Efficient Bayesian inference using adversarial machine learning and low-complexity surrogate models}}, year = {2026}, url = {https://4ort.xyz/entity/efficient-bayesian-inference-using-adversarial-machine-learning-and-low-complexity-surrogate-models}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Efficient Bayesian inference using adversarial machine learning and low-complexity surrogate models — https://4ort.xyz/entity/efficient-bayesian-inference-using-adversarial-machine-learning-and-low-complexity-surrogate-models (retrieved 2026-05-24)

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