| A truly spatial Random Forests algorithm for geoscience data analysis and modelling H Talebi, LJM Peeters, A Otto, R Tolosana-Delgado Mathematical Geosciences 54 (1), 1-22, 2022 | 61 | 2022 |
| On machine learning algorithms and compositional data R Tolosana-Delgado, H Talebi, M Khodadadzadeh, ... Proceedings of the 8th International Workshop on Compositional Data Analysis …, 2019 | 34 | 2019 |
| Geostatistical Simulation of Geochemical Compositions in the Presence of Multiple Geological Units: Application to Mineral Resource Evaluation H Talebi, U Mueller, R Tolosana-Delgado, KG van den Boogaart Mathematical Geosciences 51 (2), 129-153, 2019 | 31 | 2019 |
| Risk quantification with combined use of lithological and grade simulations: Application to a porphyry copper deposit H Talebi, EH Sabeti, M Azadi, X Emery Ore Geology Reviews 75, 42-51, 2016 | 31 | 2016 |
| Surficial and deep earth material prediction from geochemical compositions H Talebi, U Mueller, R Tolosana-Delgado, EC Grunsky, JM McKinley, ... Natural Resources Research 28 (3), 869-891, 2019 | 30 | 2019 |
| Stochastic Modelling of Mineral Exploration Targets H Talebi, U Mueller, LJM Peeters, A Otto, P de Caritat, ... Mathematical Geosciences 54 (3), 593-621, 2022 | 26 | 2022 |
| Towards geostatistical learning for the geosciences: A case study in improving the spatial awareness of spectral clustering H Talebi, LJM Peeters, U Mueller, R Tolosana-Delgado, ... Mathematical Geosciences 52 (8), 1035-1048, 2020 | 24 | 2020 |
| Simulation of the lately injected dykes in an Iranian porphyry copper deposit using the plurigaussian model H Talebi, O Asghari, X Emery Arabian Journal of Geosciences 7, 2771-2780, 2014 | 23 | 2014 |
| Joint simulation of compositional and categorical data via direct sampling technique–Application to improve mineral resource confidence H Talebi, U Mueller, R Tolosana-Delgado Computers & Geosciences 122, 87-102, 2019 | 22 | 2019 |
| Stochastic rock type modeling in a porphyry copper deposit and its application to copper grade evaluation H Talebi, O Asghari, X Emery Journal of Geochemical Exploration 157, 162-168, 2015 | 22 | 2015 |
| Application of plurigaussian simulation to delineate the layout of alteration domains in Sungun copper deposit H Talebi, O Asghari, X Emery Central European Journal of Geosciences 5 (4), 514-522, 2013 | 20 | 2013 |
| A Hybrid Model for Joint Simulation of High-Dimensional Continuous and Categorical Variables H Talebi, J Lo, U Mueller Geostatistics Valencia 2016, 415-430, 2017 | 15 | 2017 |
| Geostatistics for compositional data with R R Tolosana-Delgado, U Mueller Springer, 2021 | 12 | 2021 |
| Geostatistical semi-supervised learning for spatial prediction F Fouedjio, H Talebi Artificial Intelligence in Geosciences 3, 162-178, 2022 | 5 | 2022 |
| Stochastic modelling of mineral exploration targets. Math Geosci 54: 593–621 H Talebi, U Mueller, LJM Peeters, A Otto, P De Caritat, ... | 5 | 2022 |
| Geostatistics Valencia 2016 JJ Gómez-Hernández, J Rodrigo-Ilarri, ME Rodrigo-Clavero, E Cassiraga, ... Springer, 2017 | 5 | 2017 |
| A truly spatial random forests algorithm for geoscience data analysis and modelling. Math. Geosci. 54 (1), 1–22 H Talebi, LJM Peeters, A Otto, R Tolosana-Delgado | 4 | 2022 |
| A Truly Spatial Random Forests Algorithm for Geoscience Data Analysis and Modelling. Mathematical Geosciences, 54 (1), 1‑22 H Talebi, LJM Peeters, A Otto, R Tolosana-Delgado | 3 | 2022 |
| A truly spatial random forests algorithm for geoscience data analysis and modelling. Math Geosci 54: 1–22 H Talebi, LJM Peeters, A Otto, R Tolosana-Delgado | 3 | 2022 |
| Locally varying geostatistical machine learning for spatial prediction F Fouedjio, E Arya Artificial Intelligence in Geosciences 5, 100081, 2024 | 2 | 2024 |
Raimon Tolosana-DelgadoHelmholtz Zentrum Dresden Rossendorf, Helmholtz Institut Freiberg for Resource TechnologyEmail được xác minh tại hzdr.de