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Deep learning-based surrogate models for parametrized PDEs: Handling geometric variability through graph neural networks

Research article (Chaos An Interdisciplinary Journal of Nonlinear Science, 2023) · cited 26× · AI/ML
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Deep learning-based surrogate models for parametrized PDEs: Handling geometric variability through graph neural networks

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Deep learning-based surrogate models for parametrized PDEs: Handling geometric variability through graph neural networks is a scholarly article[1].

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  • Deep learning-based surrogate models for parametrized PDEs: Handling geometric variability through graph neural networks's instance of is recorded as scholarly article[2].

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APA 4ort.xyz Knowledge Graph. (2026). Deep learning-based surrogate models for parametrized PDEs: Handling geometric variability through graph neural networks. Retrieved May 24, 2026, from https://4ort.xyz/entity/deep-learning-based-surrogate-models-for-parametrized-pdes-handling-geometric-variability-through-graph-neural-networks
MLA “Deep learning-based surrogate models for parametrized PDEs: Handling geometric variability through graph neural networks.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/deep-learning-based-surrogate-models-for-parametrized-pdes-handling-geometric-variability-through-graph-neural-networks.
BibTeX @misc{4ortxyz_deep-learning-based-surrogate-models-for-parametrized-pdes-handling-geometric-variability-through-graph-neural-networks_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Deep learning-based surrogate models for parametrized PDEs: Handling geometric variability through graph neural networks}}, year = {2026}, url = {https://4ort.xyz/entity/deep-learning-based-surrogate-models-for-parametrized-pdes-handling-geometric-variability-through-graph-neural-networks}, note = {Accessed: 2026-05-24}}
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