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Lauzon, D. (2024). A U-Net architecture as a surrogate model combined with a geostatistical spectral algorithm for transient groundwater flow inverse problems. Advances in Water Resources, 189, 104726 (14 pages). Lien externe
Lauzon, D., & Gloaguen, E. (2024). Quantifying uncertainty and improving prospectivity mapping in mineral belts using transfer learning and Random Forest: A case study of copper mineralization in the Superior Craton Province, Quebec, Canada. Ore Geology Reviews, 166, 105918 (16 pages). Disponible
Lauzon, D. (juin 2024). Deep neural networks in surrogate hydrogeological modeling : an application for transient groundwater flow combined with a geostatistical spectral algorithm for inverse problem-solving [Résumé]. 15th International Conference on Geostatistics for Environmental Applications (GeoEnv 2024), Chania, Greece. Non disponible
Straubhaar, J., Lauzon, D., & Renard, P. (juillet 2024). Graph recurrent neural networks for stochastic simulation of Karst network topology and properties [Résumé]. 15th International Conference on Geostatistics for Environmental Applications (GeoEnv 2024), Chania, Greece. Non disponible
