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Practical Hilbert space approximate Bayesian Gaussian processes for probabilistic programming

Research article (Statistics and Computing, 2022) · cited 50× · AI/ML
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Practical Hilbert space approximate Bayesian Gaussian processes for probabilistic programming

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Practical Hilbert space approximate Bayesian Gaussian processes for probabilistic programming is a scholarly article[1].

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  • Practical Hilbert space approximate Bayesian Gaussian processes for probabilistic programming's instance of is recorded as scholarly article[2].

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Aki Vehtari Michael Riis Andersen

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  1. [2] ↑ . wikidata.org.

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  1. [1] ↑ . Wikidata. wikidata.org.

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APA 4ort.xyz Knowledge Graph. (2026). Practical Hilbert space approximate Bayesian Gaussian processes for probabilistic programming. Retrieved May 24, 2026, from https://4ort.xyz/entity/practical-hilbert-space-approximate-bayesian-gaussian-processes-for-probabilistic-programming
MLA “Practical Hilbert space approximate Bayesian Gaussian processes for probabilistic programming.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/practical-hilbert-space-approximate-bayesian-gaussian-processes-for-probabilistic-programming.
BibTeX @misc{4ortxyz_practical-hilbert-space-approximate-bayesian-gaussian-processes-for-probabilistic-programming_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Practical Hilbert space approximate Bayesian Gaussian processes for probabilistic programming}}, year = {2026}, url = {https://4ort.xyz/entity/practical-hilbert-space-approximate-bayesian-gaussian-processes-for-probabilistic-programming}, note = {Accessed: 2026-05-24}}
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