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Efficient training of physics‐informed neural networks via importance sampling

Research article (Computer-Aided Civil and Infrastructure Engineering, 2021) · cited 283× · AI/ML
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Efficient training of physics‐informed neural networks via importance sampling

Summary

Efficient training of physics‐informed neural networks via importance sampling is a scholarly article[1].

Key Facts

  • Efficient training of physics‐informed neural networks via importance sampling's instance of is recorded as scholarly article[2].

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Direct Wikidata claims

  1. [2] ↑ . wikidata.org.

Class ancestry

  1. [1] ↑ . Wikidata. wikidata.org.

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APA 4ort.xyz Knowledge Graph. (2026). Efficient training of physics‐informed neural networks via importance sampling. Retrieved May 24, 2026, from https://4ort.xyz/entity/efficient-training-of-physicsinformed-neural-networks-via-importance-sampling
MLA “Efficient training of physics‐informed neural networks via importance sampling.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/efficient-training-of-physicsinformed-neural-networks-via-importance-sampling.
BibTeX @misc{4ortxyz_efficient-training-of-physicsinformed-neural-networks-via-importance-sampling_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Efficient training of physics‐informed neural networks via importance sampling}}, year = {2026}, url = {https://4ort.xyz/entity/efficient-training-of-physicsinformed-neural-networks-via-importance-sampling}, note = {Accessed: 2026-05-24}}
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