Documents publiés en "2026"

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Arega, K. A., Benoit, N., & Lauzon, D. (mai 2026). Stochastic groundwater recharge modelling in the Harricana river watershed, Québec, Canada [Affiche]. CGU and IAH-CNC Annual Meeting 2026, Halifax, Nova Scotia. Lien externe

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Brisebois, O., Lauzon, D., & Pasquier, P. (mai 2026). Investigation of a constructive geostatistical method to assimilate unused conventional data during geothermal drilling for hydraulic conductivity profiling [Communication écrite]. 15th IEA Heat Pump Conference (HPC 2026), Vienna, Austria (12 pages). Lien externe

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Dion, G., Pasquier, P., & Lauzon, D. (mai 2026). Stochastic approach to ground heat exchanger sizing accounting for weather and ground property variability [Communication écrite]. 15th IEA Heat Pump Conference (HPC 2026), Vienna, Austria (10 pages). Lien externe

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Lauzon, D. (2026). Géostatistique et géologie minière [Notes de cours]. Lien externe

Lauzon, D., Hörning, S., & Bàrdossy, A. (2026). A generalized FFTMA approach for simulating multivariate non-Gaussian random fields with spatial asymmetry. Computers & Geosciences, 212, 106157 (18 pages). Lien externe

Lauzon, D., Kfoury, M., & Langevin, M. (septembre 2026). From data to decisions: how geostatistics supports geotechnical engineering [Présentation]. Dans 79e Conférence canadienne de géotechnique (GéoQuébec 2026), Québec, Québec, Canada. Non disponible

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Paula Burgoa Tanaka, A., Renard, P., Xia Liang, X., Straubhaar, J., & Lauzon, D. (mai 2026). Fracture network modeling with graph deep learning [Résumé]. EGU General Assembly 2026, Vienna, Austria. Lien externe

Pugliese, E., Lauzon, D., Dematteis, A., Rodani, S., Benedetti, G., & Gargini, A. (2026). Risk assessment of tunnelling-induced hydrogeological interference on springs using a machine learning approach. Hydrogeology Journal, 29 pages. Disponible

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Renard, P., Straubhaar, J., Lauzon, D., & Trunz, C. (mai 2026). Karst network simulation with statistical learning [Résumé]. EGU General Assembly 2026, Vienna, Austria. Lien externe

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Tagne Nkounga, I. B., Lauzon, D., Kfoury, M., & Langevin, M. (septembre 2026). Automatic spatial inference of stratigraphic piles under non-stationary conditions from borehole data [Présentation]. Dans 79e Conférence canadienne de géotechnique (GéoQuébec 2026), Québec, Québec, Canada. Non disponible

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Xia Liang, X., Lauzon, D., Gloaguen, E., Straubhaar, J., & Renard, P. (2026). Evaluating the influence of temporal data resolution on the performance of deep neural networks for Karst groundwater forecasting. Applied Computing and Geosciences, 31, 100393 (16 pages). Lien externe