Published 2023
| Version v1.0.2
Software
Open
Prospectivity modelling of critical mineral deposits using a generative adversarial network with oversampling and positive-unlabelled bagging
- 1. EarthByte Group, School of Geosciences, The University of Sydney, Sydney, Australia
- 2. Datarock Pty Ltd, Level 3, 31 Queen Street, Melbourne, Australia
Description
Supplementary materials, including Python scripts, Jupyter Notebooks, and datasets used to create the mineral prospectivity maps presented in the paper: Farahbakhsh, E., Maughan, J., Müller, R. D. (2023) Prospectivity modelling of critical mineral deposits using a generative adversarial network with oversampling and positive-unlabelled bagging, Ore Geology Reviews, 105665.
Files
e-farahbakhsh/MPM_Gawler-v1.0.1.zip
Files
(24.9 GB)
| Name | Size | Download all |
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md5:7791395ff57b1c8e51a13d89b0b335b8
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md5:504c3f9888d3a1b8171b2ab3284aac4c
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24.8 GB | Preview Download |
Additional details
Related works
- Is supplement to
- Software: https://github.com/e-farahbakhsh/MPM_Gawler/tree/v1.0.1 (URL)
Software
- Repository URL
- https://github.com/EarthByte/MPM_Lachlan_Laterite
- Programming language
- Python
- Development Status
- Active