Web: http://arxiv.org/abs/2204.13731

June 17, 2022, 1:11 a.m. | Yinan Feng, Yinpeng Chen, Shihang Feng, Peng Jin, Zicheng Liu, Youzuo Lin

cs.LG updates on arXiv.org arxiv.org

Inversion techniques are widely used to reconstruct subsurface physical
properties (e.g., velocity, conductivity) from surface-based geophysical
measurements (e.g., seismic, electric/magnetic (EM) data). The problems are
governed by partial differential equations (PDEs) like the wave or Maxwell's
equations. Solving geophysical inversion problems is challenging due to the
ill-posedness and high computational cost. To alleviate those issues, recent
studies leverage deep neural networks to learn the inversion mappings from
measurements to the property directly. In this paper, we show that such a …

arxiv lg

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