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Data and code supporting the publication “The importance of realistic noise characteristics in neural network inversion of airborne electromagnetic data”
This data and code supports the following published article: Kirkby, Alison, and Miller, Craig, 2026. The importance of realistic noise characteristics in neural network inversion of airborne electromagnetic data. Geophysical Journal International.
File Size17.3 MB
Data TypeDataset
Published2026
Licensegpl-3.0-or-later
Total Views111
Total Downloads5
This data and code supports the following published article:
Kirkby, Alison, and Miller, Craig, 2026. The importance of realistic noise characteristics in neural network inversion of airborne electromagnetic data. Geophysical Journal International.
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Files are hosted on the source repository. Click download to access the full dataset.
Kirkby, Alison (2026). Data and code supporting the publication “The importance of realistic noise characteristics in neural network inversion of airborne electromagnetic data”. https://doi.org/10.5281/zenodo.19873064