Probabilistic deep learning model as a tool for supporting the fast simulation of a thermal–hydraulic code

Research article (Expert Systems with Applications, 2022) · cited 31× · AI/ML
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Probabilistic deep learning model as a tool for supporting the fast simulation of a thermal–hydraulic code

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Probabilistic deep learning model as a tool for supporting the fast simulation of a thermal–hydraulic code is a scholarly article[1].

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  • Probabilistic deep learning model as a tool for supporting the fast simulation of a thermal–hydraulic code's instance of is recorded as scholarly article[2].

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APA 4ort.xyz Knowledge Graph. (2026). Probabilistic deep learning model as a tool for supporting the fast simulation of a thermal–hydraulic code. Retrieved May 24, 2026, from https://4ort.xyz/entity/probabilistic-deep-learning-model-as-a-tool-for-supporting-the-fast-simulation-of-a-thermalhydraulic-code
MLA “Probabilistic deep learning model as a tool for supporting the fast simulation of a thermal–hydraulic code.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/probabilistic-deep-learning-model-as-a-tool-for-supporting-the-fast-simulation-of-a-thermalhydraulic-code.
BibTeX @misc{4ortxyz_probabilistic-deep-learning-model-as-a-tool-for-supporting-the-fast-simulation-of-a-thermalhydraulic-code_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Probabilistic deep learning model as a tool for supporting the fast simulation of a thermal–hydraulic code}}, year = {2026}, url = {https://4ort.xyz/entity/probabilistic-deep-learning-model-as-a-tool-for-supporting-the-fast-simulation-of-a-thermalhydraulic-code}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Probabilistic deep learning model as a tool for supporting the fast simulation of a thermal–hydraulic code — https://4ort.xyz/entity/probabilistic-deep-learning-model-as-a-tool-for-supporting-the-fast-simulation-of-a-thermalhydraulic-code (retrieved 2026-05-24)

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