A Hierarchical Clustering Method for Multivariate Geostatistical Data F Fouedjio Spatial Statistics 18, 333-351, 2016 | 74 | 2016 |
Estimation of Space Deformation Model for Non-stationary Random Functions F Fouedjio, N Desassis, T Romary Spatial Statistics 13, 45-61, 2015 | 51 | 2015 |
A Generalized Convolution Model and Estimation for Non-stationary Random Functions F Fouedjio, N Desassis, J Rivoirard Spatial Statistics 16, 35-52, 2016 | 48 | 2016 |
Exploring Prediction Uncertainty of Spatial Data in Geostatistical and Machine Learning Approaches F Fouedjio, J Klump Environmental Earth Sciences 78 (1), 78-38, 2019 | 45 | 2019 |
Second-order Non-stationary Modeling Approaches for Univariate Geostatistical Data F Fouedjio Stochastic Environmental Research and Risk Assessment 31 (8), 1887–1906, 2016 | 43 | 2016 |
Geostatistical Clustering as an Aid for Ore Body Domaining: Case Study at the Rocklea Dome Channel Iron Ore Deposit, Western Australia F Fouedjio, EJ Hill, C Laukamp Applied Earth Science, TIMM B, Vol. 127 (1), pp. 15-29, 2017 | 38 | 2017 |
Exact Conditioning of Regression Random Forest for Spatial Prediction F Fouedjio Artificial Intelligence in Geosciences 1, 11-23, 2020 | 25 | 2020 |
A Spectral Clustering Approach for Multivariate Geostatistical Data F Fouedjio International Journal of Data Science and Analytics 4 (4), 301–312, 2017 | 17 | 2017 |
A geostatistical implicit modeling framework for uncertainty quantification of 3D geo-domain boundaries: Application to lithological domains from a porphyry copper deposit F Fouedjio, C Scheidt, L Yang, P Achtziger-Zupančič, J Caers Computers & Geosciences 157, 104931, 2021 | 14 | 2021 |
Clustering of multivariate geostatistical data F Fouedjio Wiley Interdisciplinary Reviews: Computational Statistics 12 (5), e1510, 2020 | 13 | 2020 |
A Fully Non-stationary Linear Coregionalization Model for Multivariate Random Fields F Fouedjio Stochastic Environmental Research and Risk Assessment 32 (6), 1699–1721, 2017 | 10 | 2017 |
Predictive geological mapping using closed-form non-stationary covariance functions with locally varying anisotropy: case study at El Teniente Mine (Chile) F Fouedjio, S Séguret Natural Resources Research 25 (4), 431-443, 2016 | 10 | 2016 |
A Clustering Approach for Discovering Intrinsic Clusters in Multivariate Geostatistical Data F Fouedjio In Perner, P. (Eds.): Machine Learning and Data Mining in Pattern …, 2016 | 10 | 2016 |
Space Deformation Non-stationary Geostatistical Approach for Prediction of Geological Objects: Case Study at El Teniente Mine (Chile) F Fouedjio Natural Resources Research 25 (3), 283-296, 2015 | 9 | 2015 |
Conditional Simulation of Categorical Spatial Variables using Gibbs Sampling of a Truncated Multivariate Normal Distribution Subject to Linear Inequality Constraints F Fouedjio, C Scheidt, L Yang, Y Wang, J Caers Stochastic Environmental Research and Risk Assessment, 2020 | 8 | 2020 |
Discovering Spatially Contiguous Clusters in Multivariate Geostatistical Data Through Spectral Clustering F Fouedjio In J. Li et al. (Eds.): Advanced Data Mining and Applications. ADMA 2016 …, 2016 | 8 | 2016 |
Classification random forest with exact conditioning for spatial prediction of categorical variables F Fouedjio Artificial Intelligence in Geosciences 2, 82-95, 2021 | 7 | 2021 |
A Spectral Clustering Method for Large-Scale Geostatistical Datasets F Fouedjio In Perner, P. (Ed.) : Machine Learning and Data Mining in Pattern …, 2017 | 5 | 2017 |
Random forest for spatial prediction of censored response variables F Fouedjio Artificial Intelligence in Geosciences 2, 115-127, 2022 | 3 | 2022 |
Encyclopedia of mathematical geosciences BSD Sagar, Q Cheng, J McKinley, F Agterberg Springer Nature, 2023 | 2 | 2023 |