AI RESEARCH
Three-dimensional inversion of gravity data using implicit neural representations and scientific machine learning
arXiv CS.LG
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ArXi:2510.17876v2 Announce Type: replace-cross Inversion of gravity data is an important method for investigating subsurface density variations relevant to mineral exploration, geothermal assessment, carbon storage, natural hydrogen, groundwater resources, and tectonic evolution. Here we present a scientific machine-learning approach for three-dimensional gravity inversion that represents subsurface density as a continuous field using an implicit neural representation