• Corpus ID: 239998322

Failure-averse Active Learning for Physics-constrained Systems

@article{Lee2021FailureaverseAL,
  title={Failure-averse Active Learning for Physics-constrained Systems},
  author={Cheolhei Lee and Xing Wang and Jianguo Wu and Xiaowei Yue},
  journal={ArXiv},
  year={2021},
  volume={abs/2110.14443}
}
Active learning is a subfield of machine learning that is devised for design and modeling of systems with highly expensive sampling costs. Industrial and engineering systems are generally subject to physics constraints that may induce fatal failures when they are violated, while such constraints are frequently underestimated in active learning. In this paper, we develop a novel active learning method that avoids failures considering implicit physics constraints that govern the system. The… 

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