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CENN: Conservative energy method based on neural networks with subdomains for solving variational problems involving heterogeneous and complex geometries
Research article (Computer Methods in Applied Mechanics and Engineering, 2022) · cited 74× · AI/ML
CENN: Conservative energy method based on neural networks with subdomains for solving variational problems involving heterogeneous and complex geometries
Summary
CENN: Conservative energy method based on neural networks with subdomains for solving variational problems involving heterogeneous and complex geometries is a scholarly article[1].
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CENN: Conservative energy method based on neural networks with subdomains for solving variational problems involving heterogeneous and complex geometries's instance of is recorded as scholarly article[2].
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APA4ort.xyz Knowledge Graph. (2026). CENN: Conservative energy method based on neural networks with subdomains for solving variational problems involving heterogeneous and complex geometries. Retrieved May 24, 2026, from https://4ort.xyz/entity/cenn-conservative-energy-method-based-on-neural-networks-with-subdomains-for-solving-variational-problems-involving-hete
MLA“CENN: Conservative energy method based on neural networks with subdomains for solving variational problems involving heterogeneous and complex geometries.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/cenn-conservative-energy-method-based-on-neural-networks-with-subdomains-for-solving-variational-problems-involving-hete.
BibTeX@misc{4ortxyz_cenn-conservative-energy-method-based-on-neural-networks-with-subdomains-for-solving-variational-problems-involving-hete_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{CENN: Conservative energy method based on neural networks with subdomains for solving variational problems involving heterogeneous and complex geometries}}, year = {2026}, url = {https://4ort.xyz/entity/cenn-conservative-energy-method-based-on-neural-networks-with-subdomains-for-solving-variational-problems-involving-hete}, note = {Accessed: 2026-05-24}}
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