Search

Copyright of Anuario do Instituto de Geociencias is the property of Universidade Federal do Rio de Janeiro, Instituto de Geociencias and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

A variational Gaussian process (VGP) model for implicit geological modeling is proposed, capable of modeling linear and non-linear trends. A new likelihood capable of honoring geological boundaries is introduced, and its performance is compared with the radial basis function (RBF) model. The model is tested on two case studies in mining, one of which relies only on photogrammetric data. The new approach generates more realistic surfaces on qualitative terms and provides an uncertainty measure. It is available as an open-source Python package. • A variational Gaussian process model for implicit geological modeling. • The model uses only discrete labels, not needing signed distances. • Anisotropy parameters can be learned semi-automatically. • Support for linear and non-linear trends. • A data-driven uncertainty measure is provided. [ABSTRACT FROM AUTHOR]