9 citations as recorded by crossref.

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7. About the trustworthiness of physics-based machine learning – considerations for geomechanical applications D. Degen et al. 10.5194/se-16-477-2025
8. Novel physics informed-neural networks for estimation of hydraulic conductivity of green infrastructure as a performance metric by solving Richards–Richardson PDE M. Elkhadrawi et al. 10.1007/s00521-023-09378-z
9. Toward Understanding the Benefits of Neural Network Parameterizations in Geophysical Inversions: A Study With Neural Fields A. Xu & L. Heagy 10.1109/TGRS.2025.3583970