Research

Our work

Featured Research

SIS

Stochastic Image Spectroscopy

IDS-ALGES Collaboration

Information and Decision Systems

ESI

Ensemble Spatial Interpolation

Scientific Publications

Journal Articles

  • [1]
    Understanding encoder–decoder structures in machine learning using information measures.
    Silva, J.F., Faraggi, V., Ramirez, C., Egaña, A. and Pavez, E.
    In Signal Processing, vol. 234, p. 109983, 2025.
  • [2]
    Optimizing infill drill hole decisions while capturing the spatial continuity of geochemical and geometallurgical properties: Application to Gol Gohar iron ore mine, Iran.
    Aghlan, M.H., Asghari, O. and Emery, X.
    In Minerals, vol. 15, no. 5, p. 478, 2025.
  • [3]
    Neural networks for parameter estimation in geostatistical models with geometric anisotropies.
    Villazón, A., Alegrı́a A. and Emery, X.
    In Machine Learning: Science and Technology, vol. 6, no. 2, p. 025025, 2025.
  • [4]
    Fuzzy classification of mineral resources: Moving towards overlapping categories to account for geological, economic, metallurgical, environmental, and operational criteria.
    Mery, N., Maleki, M., Paı́s G., Molina, A., Cáceres, A. and Emery, X.
    In Natural Resources Research, vol. 34, no. 3, pp. 1271–1299, 2025.
  • [5]
    Rudin’s extension theorems and exponential convexity for matrix- and function-valued positive semidefinite functions.
    Porcu, E., Emery, X., Ferreira, V. and Zubelli, J.
    In Computational and Applied Mathematics, vol. 44, p. 12, 2025.
  • [6]
    Stochastic image spectroscopy: a discriminative generative approach to hyperspectral image modelling and classification.
    Egaña, A.F., Ehrenfeld, A., Curotto, F., Sánchez-Pérez, J.F. and Silva, J.F.
    In Scientific Reports, vol. 14, no. 1, p. 19308, 2024.
  • [7]
    Non-monotonic transformation for Gaussianization of regionalized variables: Conditional simulation.
    Khorram, F., Emery, X., Maleki, M. and Paı́s G.
    In Natural Resources Research, vol. 33, no. 6, pp. 2589–2607, 2024.
  • [8]
    Non-monotonic transformation for Gaussianization of regionalized variables: Modeling aspects.
    Khorram, F., Emery, X., Maleki, M. and Paı́s G.
    In Natural Resources Research, vol. 33, no. 6, pp. 2567–2588, 2024.
  • [9]
    Geochemical anomaly separation based on geology, geostatistics, compositional data and local singularity analyses: A case study from the Kuh Panj copper deposit, Iran.
    Aghahadi, M.H., Jozanikohan, G., Asghari, O., Hosseini, S.T., Emery, X. and Rezaei, M.
    In Applied Geochemistry, vol. 173, p. 106135, 2024.
  • [10]
    Vector-valued Gaussian processes on non-Euclidean product spaces: Constructive methods and fast simulations based on partial spectral inversion.
    Emery, X., Mery, N. and Porcu, E.
    In Stochastic Environmental Research and Risk Assessment, vol. 38, no. 9, pp. 3411–3428, 2024.
  • [11]
    Extending the generalized Wendland covariance model.
    Bevilacqua, M., Emery, X. and Faouzi, T.
    In Electronic Journal of Statistics, vol. 18, no. 2, pp. 2771–2797, 2024.
  • [12]
    Mineral resources evaluation in narrow deposits: A case study on a layered bauxite deposit.
    Maleki, M., Mery, N., Soltani-Mohammadi, S. and Emery, X.
    In Natural Resources Research, vol. 33, pp. 1471–1490, 2024.
  • [13]
    Positive semidefinite kernels that are axially symmetric on the sphere and stationary in time: Spectral and semi-spectral theory, and constructive approaches.
    Emery, X., Jäger, J. and Porcu, E.
    In Stochastic Environmental Research and Risk Assessment, vol. 38, no. 6, pp. 2315–2329, 2024.
  • [14]
    Classifying rock types by geostatistics and random forests in tandem.
    Dutta, P.J. and Emery, X.
    In Machine Learning: Science and Technology, vol. 5, no. 2, p. 025013, 2024.
  • [15]
    Matrix-valued isotropic covariance functions with local extrema.
    Alegrı́a A. and Emery, X.
    In Journal of Multivariate Analysis, vol. 200, p. 105250, 2024.
  • [16]
    Integral representations, extension theorems and walks through dimensions under radial exponential convexity.
    Emery, X. and Porcu, E.
    In Computational and Applied Mathematics, vol. 43, no. 1, p. 28, 2024.
  • [17]
    Froth Images from Flotation Laboratory Test in Magotteaux Cell.
    Yantén, C., Kracht, W., Dı́az Gonzalo, Lois-Morales Pı́a and Egaña, A.
    In Data, vol. 8, no. 4, 2023.
  • [18]
    Assessing the uncertainty in lithology, grades and recoverable resources in an iron deposit in Southern Cameroon.
    Essoh-Ekolle, F., Emery, X. and Meying, A.
    In Natural Resources Research, vol. 32, no. 6, pp. 2515–2540, 2023.
  • [19]
    HIDSAG: Hyperspectral Image Database for Supervised Analysis in Geometallurgy.
    Ehrenfeld, A., Egaña, Á.F., Santibañez-Leal, F., Garrido, F., Ojeda, M., Townley, B. and Navarro, F.
    In Scientific Data, vol. 10, no. 1, p. 164, Mar. 2023.
  • [20]
    Subsurface Insights of the Maricunga Gold Belt through Local Earthquake Tomography.
    Bugueño, F., Calle-Gardella, D., Comte, D., Reyes-Wagner, V., Ojeda, M., Rietbrock, A. and Roecker, S.
    In Minerals, vol. 12, no. 11, 2022.
  • [21]
    Geochemical, mineralogical and geostatistical modelling of an IOCG tailings deposit (El Buitre, Chile): Implications for environmental safety and economic potential.
    González-Dı́az Erika, Garcı́a Sebastián, Soto, F., Navarro, F., Townley, B. and Caraballo, M.A.
    In Journal of Geochemical Exploration, vol. 239, p. 106997, 2022.
  • [22]
    Transitive kriging for modeling tailings deposits: A case study in southwest Finland.
    Soto, F., Navarro, F., Dı́az Gonzalo, Emery, X., Parviainen, A. and Egaña, Álvaro.
    In Journal of Cleaner Production, vol. 374, p. 133857, 2022.
  • [23]
    Modeling the Uncertainty in the Layout of Geological Units by Implicit Boundary Simulation Accounting for a Preexisting Interpretive Geological Model.
    Ferrer, R., Emery, X., Maleki, M. and Navarro, F.
    In Natural Resources Research, vol. 30, no. 6, pp. 4123–4145, 2021.
  • [24]
    Algorithm 1013: An R Implementation of a Continuous Spectral Algorithm for Simulating Vector Gaussian Random Fields in Euclidean Spaces.
    Arroyo, D. and Emery, X.
    In ACM Transactions on Mathematical Software, vol. 47, no. 1, 2021.
  • [25]
    Bivariate Matérn covariances with cross-dimple for modeling coregionalized variables.
    Alegria, A., Emery, X. and Porcu, E.
    In Spatial Statistics, vol. 41, p. 100491, 2021.
  • [26]
    Ensemble Spatial Interpolation: A New Approach to Natural or Anthropogenic Variable Assessment.
    Egaña, A., Navarro, F., Maleki, M., Grandon, F., Carter, F. and Soto, F.
    In Natural Resources Research, 2021.
  • [27]
    Geostatistical simulation of rock physical and geochemical properties with spatial filtering and its application to predictive geological mapping.
    Adeli, A. and Emery, X.
    In Journal of Geochemical Exploration, vol. 220, p. 106661, 2021.
  • [28]
    Integration of geostatistical modeling into discrete event simulation for development of tailings dam retreatment applications.
    Wilson, R., Toro, N., Naranjo, O., Emery, X. and Navarra, A.
    In Minerals Engineering, vol. 164, p. 106814, 2021.
  • [29]
    Regionalized Classification of Geochemical Data with Filtering of Measurement Noises for Predictive Lithological Mapping.
    Guartán, J.A. and Emery, X.
    In Natural Resources Research, vol. 30, no. 2, pp. 1033–1052, 2021.
  • [30]
    Simultaneous multi-sector block cave mine production scheduling considering operational uncertainties.
    Paravarzar, S., Askari-Nasab, H., Pourrahimian, Y. and Emery, X.
    In Mining Technology, vol. 130, no. 1, pp. 36–51, 2021.
  • [31]
    Using geotechnical scenarios for underground structure analysis: A case study in a hydroelectric complex in northern Portugal.
    Pinheiro, M., Emery, X., Miranda, T., Lamas Luı́s and Espada, M.
    In Tunnelling and Underground Space Technology, vol. 111, p. 103855, 2021.
  • [32]
    Predictive lithological mapping based on geostatistical joint modeling of lithology and geochemical element concentrations.
    Guartán, J.A. and Emery, X.
    In Journal of Geochemical Exploration, vol. 227, p. 106810, 2021.
  • [33]
    A robust stochastic approach to mineral hyperspectral analysis for geometallurgy.
    Egaña, Á.F., Santibáñez-Leal, F.A., Vidal, C., Díaz, G., Liberman, S. and Ehrenfeld, A.
    In Minerals, vol. 10, no. 12, pp. 1–32, 2020.
  • [34]
    A spectral algorithm to simulate nonstationary random fields on spheres and multifractal star-shaped random sets.
    Emery, X. and Alegría, A.
    In Stochastic Environmental Research and Risk Assessment, vol. 34, no. 12, pp. 2301–2311, 2020.
  • [35]
    Assessing the impact of geologic contact dilution in ore/waste classification in the gol-gohar iron ore mine, Southeastern Iran.
    Masoumi, I., Kamali, G., Asghari, O. and Emery, X.
    In Minerals, vol. 10, no. 4, 2020.
  • [36]
    Geological Facies Recovery Based on Weighted L - Regularization.
    Calderon, H., Santibañez, F., Silva, J.F., Ortiz, J.M. and Egaña, A.
    In Mathematical Geosciences, vol. 52, no. 5, pp. 593–617, 2020.
  • [37]
    Geostatistics in the presence of geological boundaries: Exploratory tools for contact analysis.
    Maleki, M. and Emery, X.
    In Ore Geology Reviews, vol. 120, 2020.
  • [38]
    Iterative algorithms for non-conditional and conditional simulation of Gaussian random vectors.
    Arroyo, D. and Emery, X.
    In Stochastic Environmental Research and Risk Assessment, vol. 34, no. 10, pp. 1523–1541, 2020.
  • [39]
    Operational mine planning in block cave mining: a simulation-optimisation approach.
    Paravarzar, S., Askari-Nasab, H., Pourrahimian, Y. and Emery, X.
    In International Journal of Mining, Reclamation and Environment, 2020.
  • [40]
    Regionalized Classification of Geochemical Data with Filtering of Measurement Noises for Predictive Lithological Mapping.
    Guartán, J.A. and Emery, X.
    In Natural Resources Research, 2020.
  • [41]
    Revalorization of Haveri Au-Cu mine tailings (SW Finland) for potential reprocessing.
    Parviainen, A., Soto, F. and Caraballo, M.A.
    In Journal of Geochemical Exploration, vol. 218, p. 106614, 2020.
  • [42]
    Simulating space-time random fields with nonseparable Gneiting-type covariance functions.
    Allard, D., Emery, X., Lacaux, C. and Lantuéjoul, C.
    In Statistics and Computing, vol. 30, no. 5, pp. 1479–1495, 2020.
  • [43]
    Stein hypothesis and screening effect for covariances with compact support.
    Porcu, E., Zastavnyi, V., Bevilacqua, M. and Emery, X.
    In Electronic Journal of Statistics, vol. 14, no. 2, pp. 2510–2528, 2020.
  • [44]
    The turning arcs: a computationally efficient algorithm to simulate isotropic vector-valued Gaussian random fields on the d-sphere.
    Alegría, A., Emery, X. and Lantuéjoul, C.
    In Statistics and Computing, vol. 30, no. 5, pp. 1403–1418, 2020.
  • [45]
    Variogram-Based Descriptors for Comparison and Classification of Rock Texture Images.
    Díaz, G.F., Ortiz, J.M., Silva, J.F., Lobos, R.A. and Egaña, Á.F.
    In Mathematical Geosciences, vol. 52, no. 4, pp. 451–476, 2020.
  • [46]
    Stochastic open-pit mine production scheduling: A case study of an iron deposit.
    Maleki, M., Jélvez, E., Emery, X. and Morales, N.
    In Minerals, vol. 10, no. 7, pp. 1–19, 2020.
  • [47]
    5D geostatistics for directional variables: Application in geotechnics to the simulation of the linear discontinuity frequency.
    Sánchez, L.K., Emery, X. and Séguret, S.A.
    In Computers and Geosciences, vol. 133, 2019.
  • [48]
    A comparison of search strategies to design the cokriging neighborhood for predicting coregionalized variables.
    Madani, N. and Emery, X.
    In Stochastic Environmental Research and Risk Assessment, vol. 33, no. 1, pp. 183–199, 2019.
  • [49]
    A geostatistical approach to estimating the parameters of a 3D Cox-Boolean discrete fracture network from 1D and 2D sampling observations.
    Hekmatnejad, A., Emery, X. and Elmo, D.
    In International Journal of Rock Mechanics and Mining Sciences, vol. 113, pp. 183–190, 2019.
  • [50]
    A semiparametric class of axially symmetric random fields on the sphere.
    Emery, X., Porcu, E. and Bissiri, P.G.
    In Stochastic Environmental Research and Risk Assessment, vol. 33, no. 10, pp. 1863–1874, 2019.
  • [51]
    A turning bands method for simulating isotropic Gaussian random fields on the sphere.
    Emery, X., Furrer, R. and Porcu, E.
    In Statistics and Probability Letters, vol. 144, pp. 9–15, 2019.
  • [52]
    Change of support using non-additive variables with Gibbs Sampler: Application to metallurgical recovery of sulphide ores.
    Garrido, M., Ortiz, J.M., Villaseca, F., Kracht, W., Townley, B. and Miranda, R.
    In Computers & Geosciences, vol. 122, pp. 68–76, 2019.
  • [53]
    Comparing linear and non-linear kriging for grade prediction and ore/waste classification in mineral deposits.
    Hekmatnejad, A., Emery, X. and Alipour-Shahsavari, M.
    In International Journal of Mining, Reclamation and Environment, vol. 33, no. 4, pp. 247–264, 2019.
  • [54]
    Geostatistics in the presence of geological boundaries: Application to mineral resources modeling.
    Emery, X. and Maleki, M.
    In Ore Geology Reviews, 2019.
  • [55]
    Nonparametric Geostatistical Simulation of Subsurface Facies: Tools for Validating the Reproduction of, and Uncertainty in, Facies Geometry.
    Madani, N., Maleki, M. and Emery, X.
    In Natural Resources Research, vol. 28, no. 3, pp. 1163–1182, 2019.
  • [56]
    Simulating isotropic vector-valued Gaussian random fields on the sphere through finite harmonics approximations.
    Emery, X. and Porcu, E.
    In Stochastic Environmental Research and Risk Assessment, vol. 33, no. 8-9, pp. 1659–1667, 2019.
  • [57]
    A path-level exact parallelization strategy for sequential simulation.
    Peredo, O.F., Baeza, D., Ortiz, J.M. and Herrero, J.R.
    In Computers & Geosciences, Jan. 2018.
  • [58]
    Admissible nested covariance models over spheres cross time.
    Peron, A., Porcu, E. and Emery, X.
    In Stochastic Environmental Research and Risk Assessment, vol. 32, no. 11, pp. 3053–3066, 2018.
  • [59]
    Geological modelling and validation of geological interpretations via simulation and classification of quantitative covariates.
    Adeli, A., Emery, X. and Dowd, P.
    In Minerals, vol. 8, no. 1, 2018.
  • [60]
    Modelling geotechnical heterogeneities using geostatistical simulation and finite differences analysis.
    Pinheiro, M., Emery, X., Miranda, T., Lamas, L. and Espada, M.
    In Minerals, vol. 8, no. 2, 2018.
  • [61]
    On a continuous spectral algorithm for simulating non-stationary Gaussian random fields.
    Emery, X. and Arroyo, D.
    In Stochastic Environmental Research and Risk Assessment, 2018.
  • [62]
    Simulation of intrinsic random fields of order k with a continuous spectral algorithm.
    Arroyo, D. and Emery, X.
    In Stochastic Environmental Research and Risk Assessment, vol. 32, no. 11, pp. 3245–3255, 2018.
  • [63]
    Robust estimation of the fracture diameter distribution from the true trace length distribution in the Poisson-disc discrete fracture network model.
    Hekmatnejad, A., Emery, X. and Vallejos, J.A.
    In Computers and Geotechnics, vol. 95, pp. 137–146, 2018.
  • [64]
    A comparison between ACO and Dijkstra algorithms for optimal ore concentrate pipeline routing.
    Baeza, D., Ihle, C.F. and Ortiz, J.M.
    In Journal of Cleaner Production, vol. 144, pp. 149–160, Feb. 2017.
  • [65]
    Recovering Latent Signals from a Mixture of Measurements Using a Gaussian Process Prior.
    Tobar, F., Rios, G. and Valdivia, T.
    In IEEE Signal Processing Letters, vol. 24, pp. 231–235, Feb. 2017.
  • [66]
    Textural image classification of foams based on variographic analysis.
    Mesa, D., Kracht, W. and Diaz, G.
    In Minerals Engineering, vol. 98, pp. 52–59, 2016.
  • [67]
    Application of joint conditional simulation to uncertainty quantification and resource classification.
    Tajvidi, E., Monjezi, M., Asghari, O., Emery, X. and Foroughi, S.
    In Arabian Journal of Geosciences, vol. 8, no. 1, pp. 455–463, 2015.
  • [68]
    Comparing sequential Gaussian and turning bands algorithms for cosimulating grades in multi-element deposits.
    Paravarzar, S., Emery, X. and Madani, N.
    In Comptes Rendus Geoscience, vol. 347, no. 2, pp. 84–93, 2015.
  • [69]
    Joint Simulation of Grade and Rock Type in a Stratabound Copper Deposit.
    Maleki, M. and Emery, X.
    In Mathematical Geosciences, vol. 47, no. 4, pp. 471–495, 2015.
  • [70]
    Stochastic rock type modeling in a porphyry copper deposit and its application to copper grade evaluation.
    Talebi, H., Asghari, O. and Emery, X.
    In Journal of Geochemical Exploration, vol. 157, pp. 162–168, 2015.
  • [71]
    Reconstruction of channelized geological facies based on RIPless compressed sensing.
    Calderon, H., Silva, J.F., Ortiz, J.M. and Egana, A.
    In Computers & Geosciences, vol. 77, pp. 55–65, 2015.
  • [72]
    Can a training image be a substitute for a random field model?
    Emery, X. and Lantuejoul, C.
    In Mathematical Geosciences, vol. 46, no. 2, pp. 133–147, 2014.
  • [73]
    Capping and kriging grades with long-tailed distributions.
    Maleki, M., Madani, N. and Emery, X.
    In Journal of the Southern African Institute of Mining and Metallurgy, vol. 114, no. 3, pp. 255–263, 2014.
  • [74]
    Designing and Advanced RC Drilling Grid for Short-Term Planning in Open Pit Mines: Three Case Studies.
    Ortiz, J.M. and Magri, E.J.
    In The Journal of the Southern African Institute of Mining and Metallurgy, vol. 114, no. 8, pp. 631–639, 2014.
  • [75]
    Fast update of conditional simulation ensembles.
    Chevalier, C., Emery, X. and Ginsbourger, D.
    In Mathematical Geosciences, pp. 1–19, 2014.
  • [76]
    Multiple-Point Geostatistical Simulation of Dykes: Application at Sungun Porphyry Copper System, Iran.
    Rezaee, H., Asghari, O., Koneshloo, M. and Ortiz, J.M.
    In Stochastic Environmental Research and Risk Assessment, pp. 1–15, 2014.
  • [77]
    Simulation of the lately injected dykes in an Iranian porphyry copper deposit using the plurigaussian model.
    Talebi, H., Asghari, O. and Emery, X.
    In Arabian Journal of Geosciences, vol. 7, no. 7, pp. 2771–2780, 2014.
  • [78]
    Tuning and Hybrid Parallelization of a Genetic-based Multi-Point Statistics Simulation Code.
    Peredo, O., Ortiz, J.M., Herrero, J.R. and Samaniego, C.
    In Parallel Computing, vol. 40, no. 5, pp. 144–158, 2014.
  • [79]
    Verifying the high-order consistency of training images with data for multiple-point geostatistics.
    Perez, C., Mariethoz, G. and Ortiz, J.M.
    In Computers & Geosciences, vol. 70, pp. 190–205, 2014.
  • [80]
    Simulating large Gaussian random vectors subject to inequality constraints by Gibbs sampling.
    Emery, X., Arroyo, D. and Pelaez Marı́a.
    In Mathematical Geosciences, vol. 46, no. 3, pp. 265–283, 2014.
  • [81]
    Simulation of Intrinsic Random Fields of Order k with Gaussian Generalized Increments by Gibbs Sampling.
    Arroyo, D. and Emery, X.
    In Mathematical Geosciences, pp. 1–20, 2014.
  • [82]
    A stochastic approach for measuring bubble size distribution via image analysis.
    Kracht, W., Emery, X. and Paredes, C.
    In International Journal of Mineral Processing, vol. 121, pp. 6–11, 2013.
  • [83]
    Application of plurigaussian simulation to delineate the layout of alteration domains in Sungun copper deposit.
    Talebi, H., Asghari, O. and Emery, X.
    In Open Geosciences, vol. 5, no. 4, pp. 514–522, 2013.
  • [84]
    Geostatistics applied to cross-well reflection seismic for imaging carbonate aquifers.
    Parra, J. and Emery, X.
    In Journal of Applied Geophysics, vol. 92, pp. 68–75, 2013.
  • [85]
    Integration of crosswell seismic data for simulating porosity in a heterogeneous carbonate aquifer.
    Emery, X. and Parra, J.
    In Journal of Applied Geophysics, vol. 98, pp. 254–264, 2013.
  • [86]
    Simulation of mineral grades and classification of mineral resources by using hard and soft conditioning data: application to Sungun porphyry copper deposit.
    Tehrani, M., Asghari, O. and Emery, X.
    In Arabian Journal of Geosciences, vol. 6, no. 10, pp. 3773–3781, 2013.
  • [87]
    An enhanced Gibbs sampler algorithm for non-conditional simulation of Gaussian random vectors.
    Arroyo, D., Emery, X. and Pelaez Marı́a.
    In Computers & Geosciences, vol. 46, pp. 138–148, 2012.
  • [88]
    Cokriging random fields with means related by known linear combinations.
    Emery, X.
    In Computers & Geosciences, vol. 38, no. 1, pp. 136–144, 2012.
  • [89]
    Co-simulating total and soluble copper grades in an oxide ore deposit.
    Emery, X.
    In Mathematical Geosciences, vol. 44, no. 1, pp. 27–46, 2012.
  • [90]
    Detecting and Quantifying Sources of Non-Stationarity via Experimental Semivariogram Modeling.
    Cuba, M.A., Leuangthong, O. and Ortiz, J.M.
    In Stochastic Environmental Research and Risk Assessment, vol. 26, no. 2, pp. 247–260, 2012.
  • [91]
    Enhanced coregionalization analysis for simulating vector Gaussian random fields.
    Emery, X. and Ortiz, J.M.
    In Computers & Geosciences, vol. 42, pp. 126–135, 2012.
  • [92]
    Improving financial returns from mining through geostatistical simulation and the optimized advance drilling grid at El Tesoro Copper Mine.
    Ortiz, J.M., Magri, E.J. and Libano, R.
    In Journal of the Southern African Institute of Mining and Metallurgy, vol. 112, no. 1, pp. 15–22, 2012.
  • [93]
    M. Armstrong, A. Galli, H. Beucher, G. Le Loc’h, D. Renard, B. Doligez, R. Eschard, F. Geffroy: Plurigaussian Simulations in Geosciences.
    Emery, X.
    In Mathematical Geosciences, vol. 44, no. 2, pp. 239–240, 2012.
  • [94]
    Parallel-distributed model deformation in the fingertips for stable grasping and object manipulation.
    Garcia-Rodriguez, R. and Diaz-Rodriguez, G.
    In Mathematical Problems in Engineering, vol. 2012, 2012.
  • [95]
    Transferring Sampling Errors into Geostatistical Modeling.
    Cuba, M.A., Leuangthong, O. and Ortiz, J.M.
    In Journal of the Southern African Institute of Mining and Metallurgy, vol. 112, no. 11, pp. 971–983, 2012.
  • [96]
    Using two-point set statistics to estimate the diameter distribution in Boolean models with circular grains.
    Emery, X., Kracht, W., Egana, A. and Garrido, F.
    In Mathematical Geosciences, vol. 44, no. 7, pp. 805–822, 2012.
  • [97]
    Reducing the number of orthogonal factors in linear coregionalization modeling.
    Emery, X. and Pelaez, M.
    In Computers & Geosciences, vol. 46, pp. 149–156, 2012.
  • [98]
    Multivariate resource modelling for assessing uncertainty in mine design and mine planning.
    Montoya, C., Emery, X., Rubio, E. and Wiertz, J.
    In Journal of the Southern African Institute of Mining and Metallurgy, vol. 112, no. 5, pp. 353–363, 2012.
  • [99]
    A Comparison of Random Field Models Beyond Bivariate Distributions.
    Emery, X. and Ortiz, J.M.
    In Mathematical Geosciences, vol. 43, no. 2, pp. 183–202, 2011.
  • [100]
    Adapting a Texture Synthesis Algorithm for Conditional Multiple Point Geostatistical Simulation.
    Parra, A. and Ortiz, J.M.
    In Stochastic Environmental Research and Risk Assessment, vol. 25, no. 8, pp. 1101–1111, 2011.
  • [101]
    Parallel implementation of simulated annealing to reproduce multiple-point statistics.
    Peredo, O. and Ortiz, J.M.
    In Computers & Geosciences, vol. 37, no. 8, pp. 1110–1121, 2011.
  • [102]
    Two approaches to direct block-support conditional co-simulation.
    Emery, X. and Ortiz, J.M.
    In Computers & Geosciences, vol. 37, no. 8, pp. 1015–1025, 2011.
  • [103]
    A methodology to construct training images for vein type deposits.
    Boisvert, J.B., Leuangthong, O., Ortiz, J.M. and Deutsch, C.V.
    In Computers & Geosciences, vol. 34, no. 5, pp. 491–502, 2008.
  • [104]
    Geostatistical modeling of rock type domains with spatially varying proportions: Application to a porphyry copper deposit.
    Emery, X., Ortiz, J.M. and Caceres, A.M.
    In Journal of the South African Institute of Mining and Metallurgy, vol. 108, no. 5, pp. 285–292, 2008.
  • [105]
    Local Recoverable Reserves Prediction with Block LU Simulation.
    Boisvert, J., Ortiz, J.M. and Deutsch, C.V.
    In International Journal of Mining and Mineral Engineering, vol. 1, no. 1, pp. 3–21, 2008.
  • [106]
    On the challenge of using sequential indicator simulation for the estimation of recoverable reserves.
    Machuca-Mory, D.F., Ortiz, J.M. and Deutsch, C.V.
    In International Journal of Mining, Reclamation and Environment, vol. 22, no. 4, pp. 285–299, 2008.
  • [107]
    Case for geometric criteria in resources and reserves classification, Society for Mining.
    Deutsch, C.V., Leuangthong, O. and Ortiz, J.M.
    In Transactions Society for Mining Metallurgy and Exploration Incorporated, vol. 322, pp. 1–11, 2007.
  • [108]
    FITS Files and Regular Grammars: A DMaSS Design Case Study.
    Cooke, A., Egana, A. and Lowry, S.
    In Astronomical Data Analysis Software and Systems XVI, vol. 376, p. 499, 2007.
  • [109]
    Scaling multiple-point statistics to different univariate proportions.
    Ortiz, J.M., Lyster, S. and Deutsch, C.V.
    In Computers & Geosciences, vol. 33, no. 2, pp. 191–201, 2007.
  • [110]
    Weighted sample variograms as a tool to better assess the spatial variability of soil properties.
    Emery, X. and Ortiz, J.M.
    In Geoderma, vol. 140, no. 1, pp. 81–89, 2007.
  • [111]
    Block size selection and its impact on open pit mine design and planning.
    Jara, R., Couble, A., Emery, X., Magri, E. and Ortiz, J.
    In Journal of the South African Institute of Mining and Metallurgy, vol. 106, no. 3, pp. 205–211, 2006.
  • [112]
    Geostatistical estimation of mineral resources with soft boundaries: a comparative study.
    Ortiz, J.M. and Emery, X.
    In Journal of the South African Institute of Mining and Metallurgy, vol. 106, no. 8, pp. 577–584, 2006.
  • [113]
    Geostatistical Simulation of Optimum Mining Elevations for Nickel Laterite Deposits.
    McLennan, J.A., Ortiz, J.M. and Deutsch, C.V.
    In CIM Magazine, vol. 1, no. 6, 2006.
  • [114]
    Quantifying Uncertainty in Mineral Resources by Use of Classification Schemes and Conditional Simulations.
    Emery, X., Ortiz, J.M. and Rodriguez, J.J.
    In Mathematical Geology, vol. 38, no. 4, pp. 445–464, 2006.
  • [115]
    Estimation of mineral resources using grade domains: critical analysis and a suggested methodology.
    Emery, X. and Ortiz, J.M.
    In Journal of the South African Institute of Mining and Metallurgy, vol. 105, no. 4, pp. 247–255, 2005.
  • [116]
    Histogram and Variogram Inference in the Multigaussian Model.
    Emery, X. and Ortiz, J.M.
    In Stochastic Environmental Research and Risk Assessment, vol. 19, no. 1, pp. 48–58, 2005.
  • [117]
    Resource and reserve evaluation in the presence of imprecise data.
    Emery, X., Bertini, J.P. and Ortiz, J.M.
    In CIM Bulletin, vol. 98, no. 1089, p. 2000, 2005.
  • [118]
    Indicator Simulation Accounting for Multiple-Point Statistics.
    Ortiz, J.M. and Deutsch, C.V.
    In Mathematical Geology, vol. 36, no. 5, pp. 545–565, 2004.
  • [119]
    Shortcomings of Multiple Indicator Kriging for Assessing Local Distributions.
    Emery, X. and Ortiz, J.M.
    In Applied Earth Science (Transactions of the Institutions of Mining and Metallurgy: Section B), vol. 113, no. 4, pp. 249–259, 2004.
  • [120]
    Calculation of Uncertainty in the Variogram.
    Ortiz, J. and Deutsch, C.V.
    In Mathematical Geology, vol. 34, no. 2, 2002.

Conference Articles

  • [1]
    Characterizing Probabilistic Structure in Learning Using Information Sufficiency.
    Faraggi, V., Silva, J.F., Ramı́rez Camilo, Egaña, A. and Pavez, E.
    In 2024 IEEE 34th International Workshop on Machine Learning for Signal Processing (MLSP), pp. 1–6, 2024.
  • [2]
    Geometallurgical estimation of mineral samples from hyperspectral images and statistical topic modelling.
    Santibáñez-Leal, F.A., Ehrenfeld, A., Garrido, F., Navarro, F. and F. Egaña, Álvaro.
    In Proceedings of Procemin-Geomet, Santiago, Chile2022.
  • [3]
    Resource assessment of copper mine tailings.
    Navarro, F., Soto, F., Townley, B., Caraballo, M., Garcı́a Sebastián, González, E. and Egaña, Álvaro.
    In Proceedings of Geostats2021.
  • [4]
    Implicit boundary simulation accounting for a preexisting interpretive geological model.
    Emery, X., Maleki, M., Navarro, F. and Ferrer, R.
    In Proceedings of Geostats2021.
  • [5]
    PYRAMP: A platform for resource assessment and mine planning in Jupyter.
    Morales, N., Jélvez, E., Morales, G., Soto, F., Dı́az G. and Navarro, F.
    In Proceedings of the 40th International Symposium on the Application of Computers and Operations Research in the Mineral Industry (APCOM 2021), Johannesburg, South Africa2021.
  • [6]
    Natural Gamma Rays to assist Geo Modelling.
    Farfan, L., Garrido, M. and Mendez, M.
    In International Convention, Trade Show & Investors Exchange PDAC, Toronto, Canada2018.
  • [7]
    Automatic selection of fracture sets using clustering techniques.
    Soto, F., Hekmatnejad, A., Emery, X. and Elmo, D.
    In 2nd International Discrete Fracture Network Engineering Conference, DFNE 20182018.
  • [8]
    Optimization of planning and scheduling of ore body with open pit extraction considering homogeneity in clays as geometallurgical variables.
    Garrido, M., Sepulveda, E. and Navarro, F.
    In GEOMIN-MINEPLANNING, 5th International Seminar on Geology for the Mining Industry 2017, Santiago, Chile2017.
  • [9]
    Rapid Multivariate Resource Assessment.
    Soto, F., Garrido, M., Diaz, G. and Silva, C.
    In GEOMIN-MINEPLANNING, 5th International Seminar on Geology for the Mining Industry 2017, Santiago, Chile2017.
  • [10]
    Simulation of preparation time of a TBM in the underground mining development considering rock mass variability.
    Garrido, M. and Silva, C.
    In GEOMIN-MINEPLANNING, 5th International Seminar on Geology for the Mining Industry 2017, Santiago, Chile2017.
  • [11]
    Geometallurgical Variables Characterization Using Hyperspectral Images and Machine Learning Technics.
    Ehrenfeld, A., Egana, A., Guerrero, P., Liberman, S., Hanna, V., Voisin, L. and Adams, M.
    In 38th Application of Computers and Operations Research in the Mineral Industry, pp. 61–66, 2017.
  • [12]
    Restauración 3D de Modelos Geologicos basados en un sistema Masa-Resorte.
    Ojeda, M., Vicencio, A., Baeza, D., Navarro, F. and Arriagada, C.
    In Actas XX Congreso Geologico Argentino, San Miguel de Tucuman, Argentina2017.
  • [13]
    The impact of geometric variation on the resource estimation quality using an unfolding methodology.
    Vicencio, A., Ojeda, M., Baeza, D. and Navarro, F.
    In Geomin Mineplanning 2017, 5\,^∘ seminario Internacional de Geologia para la Industria Minera, 5\,^∘ seminario Internacional de Planificacion Minera, Santiago, Chile2017.
  • [14]
    Veins resource assessment in the presence of structural non-rotational faults and folds.
    Soto, F., Ortiz, J.M., Egana, A., Garrido, M. and Baeza, D.
    In GEOSTAT 2016, Valencia, Spain2016.
  • [15]
    A case study of geometallurgical modeling of metal recovery with unequal sampling.
    Garrido, M., Navarro, F., Sepulveda, E. and Townley, B.
    In GEOMET 2016 – 3rd International Seminar on Geometallurgy2016.
  • [16]
    Abeja VGML: geometallurgical applications on cloud services.
    Barberan, A., Lopez, A., Friedrich, C., Navarro, F., Gonzalez, C., Morales, N. and Egana, A.
    In MININ 2016 – 6th International Conference on Innovations in Mine Operations2016.
  • [17]
    An immersive 3D geological and mining data visualization environment.
    Gonzalez, C., Navarro, F., Rojas, C., Gonzalez, M., Pardo, S., Comte, D., Carrizo, D., Diaz, M. and Salvo, J.
    In MININ 2016 – 6th International Conference on Innovations in Mine Operations2016.
  • [18]
    Calculating ore resources on complex geology using a geometric restitution methodology: from modeling to the estimation.
    Navarro, F., Baeza, D., Herreros, D. and Valencia, M.
    In U-Mining 2016: First International Conference on Underground Mining2016.
  • [19]
    Channelized facies recovery based on weighted compressed sensing.
    Calderon, H., Santibanez, F., Silva, J.F., Ortiz, J.M. and Egana, A.
    In Sensor Array and Multichannel Signal Processing Workshop (SAM), Rio de Janeiro, Brazil, pp. 1–5, 2016.
  • [20]
    Effect of frother type on froth texture and gas holdup.
    Mesa, D., Kracht, W. and Diaz, G.
    In Copper 2016, Kobe, Japan2016.
  • [21]
    Incorporation of geological information on unfolding and restoration of veins for ore body evaluation.
    Garrido, M., Silva, C., Becerra, J., Navarro, F. and Townley, B.
    In MININ 2016 – 6th International Conference on Innovations in Mine Operations2016.
  • [22]
    New human-computer interfaces to capture expert geological knowledge.
    Navarro, F., Diaz, G., Garrido, M., Ortiz, J.M. and Egana, A.
    In MININ 2016 – 6th International Conference on Innovations in Mine Operations2016.
  • [23]
    Progress towards Data-driven Mine Planning via a Virtual Geometallurgical Laboratory.
    Lopez, A., Barberan, A., Alarcon, M., Vargas, E., Ortiz, J.M., Morales, N., Emery, X., Egana, A., McFarlane, A. and Friedrich, C.
    In GEOMET 2016 - The Third AusIMM International Geometallurgy Conference2016.
  • [24]
    Resource assessment with unfolding methodology: a case study.
    Garrido, M., Navarro, F. and Ortiz, J.M.
    In MININ 2016 – 6th International Conference on Innovations in Mine Operations2016.
  • [25]
    Rock texture discrimination: A new tool for geological characterization.
    Diaz, G., Egana, A., Cortes, M. and Ortiz, J.M.
    In MININ 2016, Santiago, Chile2016.
  • [26]
    U-Fo: An Innovative Successful Case of Geological Resource Assessment on Gold Deposits Under Complex Geometries.
    Navarro, F., Garrido, M., Gonzalez, C., Baeza, D., Soto, F., Egana, A., Herreros, D. and Valencia, M.
    In MINEXCELLENCE 2016 – 1st International Seminar on Operational Excellence in Mining2016.
  • [27]
    Applying data science techniques to metallurgical characterization.
    Baeza, D., Navarro, F. and Townley, B.
    In GEOMET 2016 – 3rd International Seminar on Geometallurgy, Lima, Peru2016.
  • [28]
    Time Dependence of Shear Wavespeeds in Northern Chile Related to the 2014 Mw8. 3 Pisagua Earthquake.
    Comte, D., Arriaza, R. and Roecker, S.
    In AGU Fall Meeting Abstracts2016.
  • [29]
    Practical Aspects of Resources Modeling in presence of Locally Varying Anisotropy.
    Peredo, O., Garrido, M. and Ortiz, J.M.
    In IAMG 2015, Freiberg, Germany2015.
  • [30]
    Analysis and Classification of Natural Rock Textures based on New Transform-based Features.
    Lobos, R., Silva, J.F., Ortiz, J.M., Diaz, G. and Egana, A.
    In Mathematical Geosciences. Vol. 48(7), Pp. 835–8702015.
  • [31]
    CUDA-Based Implementation of GSLIB: The Geostatistical Software Library.
    Baeza, D., Peredo, O. and Ortiz, J.M.
    In GPU Technology Conference, San jose, California2015.
  • [32]
    Elastic Wavespeed Images of Northern Chile Subduction Zone from the Joint Inversion of Body and Surface Waves: Structure of the Andean Forearc and the Double Seismic Zone.
    Comte, D., Carrizo, D., Roecker, S.W., Peyrat, S., Arriaza, R.C., Chi, R.K. and Baeza, S.
    In AGU Fall Meeting Abstracts2015.
  • [33]
    High performance computing in geostatistics.
    Soto, F.
    In Big Data and Environment Workshop 20152015.
  • [34]
    Incorporating distributed Dijkstra’s algorithm into variogram calculation with locally varying anisotropy.
    Peredo, O., Navarro, F., Garrido, M. and Ortiz, J.M.
    In Proceedings of the 37th International Symposium APCOM 20152015.
  • [35]
    The September 16, 2015 Illapel (Mw 8.3) Earthquake: Comprehensive Analysis from Seismic and Geodetic Observations.
    Comte, D., Carrizo, D., Peyrat, S., Russo, R.M., Roecker, S.W., Opazo, T., Pena, G., Baeza, S., Arriaza, R.C., Ortega-Culaciati, F. and others.
    In AGU Fall Meeting Abstracts2015.
  • [36]
    U-Fo: software para la evaluacion de recursos en presencia de fallas y pliegues.
    Soto, F., Ortiz, J.M. and Garrido, M.
    In Geomin 2015, Antofagasta, Chile2015.
  • [37]
    A Flexible Strategy for Distributed and Parallel Execution of a Monolithic Large-Scale Sequential Application.
    Navarro, F., González, C., Peredo, Ó., Morales, G., Egaña, Á. and Ortiz, J.M.
    In High Performance Computing, Berlin, Heidelberg, pp. 54–67, 2014.
  • [38]
    Challenges in analysis of geo-metallurgical data: Linking numbers with interpretations.
    Ortiz, J.M.
    2014.
  • [39]
    Geochemical quantitative mineral characterization for geometallurgical applications in porphyry copper deposits.
    Cardenas, E., Townley, B., Ortiz, J.M. and Kracht, W.
    2014.
  • [40]
    Geometallurgical Modelling and Mine Planning, CSIRO Chile Program 2.
    Ortiz, J.M.
    2014.
  • [41]
    GPU parallelization of geostatistical simulation for mineral reserves quantification.
    Baeza, D., Peredo, O., Navarro, F. and Ortiz, J.M.
    In NVIDIA GPU Technology Conference2014.
  • [42]
    Inverse modeling of moving average kernels for 3D Gaussian simulation.
    Peredo, O., Ortiz, J.M. and Leuangthong, O.
    Paris, France2014.
  • [43]
    Resurrecting GSLIB by code optimization and multi-core programming.
    Peredo, O. and Ortiz, J.M.
    In Geostatistical and geospatial approaches for the characterization of natural resources in the environment: Challenges, Processes and Strategies, New Dehli, India2014.
  • [44]
    Water/rock interactions and physicochemical controls on mineral processing: being predictive based on geology.
    Lois, P., Kracht, W., Townley, B. and Ortiz, J.M.
    2014.
  • [45]
    Categorical variables simulation incorporating local varying anisotropy.
    Gutierrez, R., Ortiz, J.M. and Townley, B.
    2013.
  • [46]
    Geometric restitution for improving mineral resource estimation applied to Peumo deposit.
    Soto, F., Ortiz, J.M., Herreros, D. and Valencia, M.
    In GEOMIN 20132013.
  • [47]
    Physicochemical modeling of the behavior of different mineralogical units in milling and flotation.
    Lois, P., Townley, B., Kracht, W. and Ortiz, J.M.
    2013.
  • [48]
    Implementation of parallelized conditional simulation in GPU for generating large resources models.
    Baeza, D., Sepulveda, E. and Ortiz, J.M.
    2012.
  • [49]
    Improve an efficient simulation of multidimensional Gaussian random fields in GPU.
    Baeza, D., Sepulveda, E. and Ortiz, J.
    In V Latin American Symposium on High Performance Computing HPCLatAm, Buenos Aires, Argentina2012.
  • [50]
    Improving an efficient simulation of multidimensional Gaussian random fieldsin GPU.
    Baeza, D., Sepulveda, E. and Ortiz, J.M.
    Buenos Aires, Argentina2012.
  • [51]
    Modelamiento y simulacion del sistema de carguı́o y transporte en Mina Chuquicamata.
    Yarmuch, J.L. and Ortiz, J.M.
    2012.
  • [52]
    Multiple-point geostatistical simulation based on genetic algorithms implemented in a shared-memory supercomputer.
    Peredo, O. and Ortiz, J.M.
    Oslo, Norway, pp. 103–114, 2012.
  • [53]
    Parallel implementation of multiple-point simulation based on texture synthesis.
    Parra, A. and Ortiz, J.M.
    2012.
  • [54]
    Parallelization of simulation algorithm with GPU for constructing highresolution models of Earth Sciences variables.
    Baeza, D., Sepulveda, E. and Ortiz, J.M.
    Valencia, Spain2012.
  • [55]
    Training image selection for multiple-point geostatistical simulation.
    Perez, C., Mariethoz, G. and Ortiz, J.M.
    2012.
  • [56]
    A Novel Approach to Estimate the Gap Between the Middle and Short-Term Plans.
    Yarmuch, J.L. and Ortiz, J.M.
    WA, Australia2011.
  • [57]
    Inferring a representative distribution of soluble copper grade in the presence of a preferential sampling.
    Saa, J., Ortiz, J.M., Magri, E.J. and Emery, X.
    Santiago, Chile2011.
  • [58]
    Mine-scale modeling of lithologies with multiple-point geostatistical simulation.
    Perez, C. and Ortiz, J.M.
    Salzburg2011.
  • [59]
    Stepwise Conditional Transformation of linearly transformed variables for multivariate geostatistical simulation.
    Pizarro Sebastı́an H. A. and Ortiz, J.M.
    Santiago, Chile2011.
  • [60]
    Adding flexibility to support vector classification for modelling categorical variables.
    Cuba, M.A., Leuangthong, O. and Ortiz, J.M.
    Santiago, Chile, pp. 479–489, 2010.
  • [61]
    Conditional multiple point simulation with texture synthesis.
    Parra, A. and Ortiz, J.M.
    2010.
  • [62]
    Distributed-multiprocess implementation of kriging for the estimation of mineral resources.
    Sepulveda, E. and Ortiz, J.M.
    Santiago, Chile, pp. 433–442, 2010.
  • [63]
    Geological modelling and metallurgical prediction supported by linear and non-linear statistics.
    Carmona, S. and Ortiz, J.M.
    Santiago, Chile, pp. 459–470, 2010.
  • [64]
    Image segmentation for mineral identification in oxide copper deposit.
    Egana, A.F. and Ortiz, J.M.
    Santiago, Chile, pp. 405–412, 2010.
  • [65]
    Mine planning considering uncertainty in grades and work index.
    Contreras, R., Ortiz, J.M. and Bisso, C.
    Santiago, Chile, pp. 129–136, 2010.
  • [66]
    Multiple-point conditional unilateral simulation for categorical variables.
    Parra, A. and Ortiz, J.M.
    Santiago, Chile, pp. 413–422, 2010.
  • [67]
    Quantifying uncertainty in resources tonnage using multiple point geostatistical simulation.
    Hurtado, S. and Ortiz, J.M.
    Santiago, Chile, pp. 423–432, 2010.
  • [68]
    The economic optimisation of advanced drilling grids for short term planning and grade control at El Tesoro Copper Mine.
    Magri, E.J., Ortiz, J.M. and Libano, R.
    Santiago, Chile, pp. 89–98, 2010.
  • [69]
    Conditional multiple-point simulation with a texture synthesis algorithm, Computational Methods for the Earth, Energy and Environmental Sciences.
    Parra, A. and Ortiz, J.M.
    2009.
  • [70]
    An Overview of the Challenges of Multiple-Point Geostatistics.
    Ortiz, J.M.
    Santiago, Chilevol. 1, , pp. 11–20, 2008.
  • [71]
    Conditional multiple-point simulation with a texture synthesis algorithm.
    Parra, A.J. and Ortiz, J.M.
    2008.
  • [72]
    Geostatistics applied to geotechnical parameters.
    Egana, M., Arancibia, E., Villegas, F. and Ortiz, J.M.
    , pp. 137–146, 2008.
  • [73]
    Innovations in Software Development for Resource Evaluation.
    Ortiz, J.M., Sepulveda, E., Magri, E.J., Emery, X. and Barberan, A.
    In MININ 2008 - 4th International Conference on Innovations in Mine Operations, Santiago, Chile2008.
  • [74]
    Outlier detection and consistent h-scatter plot smoothing for robust variogram estimation.
    Ortiz, J.M. and Leuangthong, O.
    2008.
  • [75]
    A practical approach to validate the variogram reproduction from geostatistical simulation.
    Ortiz, J.M. and Leuangthong, O.
    , pp. 121–127, 2007.
  • [76]
    An Optimization Algorithm to Asses Different Resource Models for Open Pit Short Term Planning.
    Ortiz, J.M., Rubio, E. and Yarmuch, J.L.
    , pp. 721–732, 2007.
  • [77]
    Analysis of fiber optics BOTDR data to predict rock mass behavior in panel caving.
    Ortiz, J.M., Manasevich, R., Silva, D., Calderon, C. and Molina, R.
    2007.
  • [78]
    Conditional simulation as a tool for assessing mining selectivity.
    Emery, X. and Ortiz, J.M.
    , pp. 79–85, 2007.
  • [79]
    Geostatistical simulation of mineral grades in the presence of spatial trends.
    Robles, L., Emery, X. and Ortiz, J.M.
    In 33rd International Symposium on Applications of Computers and Operations Research in the Mineral Industry APCOM, pp. 87–93, 2007.
  • [80]
    Integration of Disparate Data with Logratios of Conditional Probabilities.
    Hong, S., M., O.J. and Deutsch, C.V.
    2007.
  • [81]
    VOTable Construction and a Simple, Lazy, Expression Evaluator: Two Technical Aspects of the DMaSS.
    Egana, A.
    In Astronomical Data Analysis Software and Systems XVIvol. 376, , p. 506, 2007.
  • [82]
    A comparative study of three data-driven Mineral Potential Mapping techniques.
    Caumon, G., Ortiz, J.M. and Rabeau, O.
    Belgium2006.
  • [83]
    Evaluacion de la incertidumbre en la variabilidad espacial de la precipitacion usando un modelamiento multiGaussiano.
    Dussaubat, S., Vargas, X. and Ortiz, J.M.
    2006.
  • [84]
    Multivariate geostatistical and GIS methods for mineral exploration.
    Ortiz, J.M. and Caumon, G.
    Santiago, Chile2006.
  • [85]
    Multivariate p-field simulation.
    Ortiz, J.M.
    2006.
  • [86]
    A Step by Step Guide to Bi-Gaussian Disjunctive Kriging.
    Ortiz, J.M., Oz, B. and Deutsch, C.V.
    In Geostatistics Banff 2004vol. 2, , pp. 1097–1102, 2005.
  • [87]
    Estimacion de la variabilidad espacial de eventos de precipitacion usando metodos geoestadisticos.
    Dussaubat, S., Vargas, X. and Ortiz, J.M.
    2005.
  • [88]
    Integrating Multiple-Point Statistics into Sequential Simulation Algorithms.
    Ortiz, J.M. and Emery, X.
    vol. 2, , pp. 969–978, 2005.
  • [89]
    Internal Consistency and Inference of Change-of-support isofactorial Models.
    Emery, X. and Ortiz, J.M.
    In Geostatistics Banff 2004vol. 2, , pp. 1057–1066, 2005.
  • [90]
    On the Scaling and Use of Multivariate Distributions in Geostatistical Simulation.
    Leuangthong, O., Ortiz, J.M. and Deutsch, C.V.
    Toronto, Canada2005.
  • [91]
    Simulacion geoestadistica por campos de probabilidad para evaluacion de reservas mineras.
    Ortiz, J.M.
    Buenos Aires, Argentina2005.
  • [92]
    A MultiGaussian Approach to Assess Block Grade Uncertainty.
    Ortiz, J.M., Leuangthong, O. and Deutsch, C.V.
    2004.
  • [93]
    Categorizacion de Recursos y Reservas Mineras.
    Ortiz, J.M. and Emery, X.
    , pp. 226–236, 2004.
  • [94]
    Geostatistical Simulation of Optimum Mining Elevations for Nickel Laterite Deposits.
    McLennan, J.A., Ortiz, J.M. and Deutsch, C.V.
    2004.
  • [95]
    Modelamiento Geoestadistico de la Razon de Solubilidad en un Yacimiento de Oxidados de Cobre.
    Emery, X., Carrasco, P. and Ortiz, J.M.
    , pp. 198–208, 2004.
  • [96]
    Hierarchical Indicator Simulation.
    Ortiz, J. and Deutsch, C.V.
    Phoenix, Arizona, pp. 275–284, 2002.
  • [97]
    Estimation of Economic Losses due to Poor Blast Hole Sampling in Open Pits.
    Magri, E.J. and Ortiz, J.M.
    In Geostatistics 2000, Cape Town, South Africavol. 2, , pp. 732–741, 2000.

Theses

  • [1]Habilitación de sistema de análisis hı́per espectral para aplicaciones con paneo, Memoria de Pregrado, Pontificia Universidad Católica de Chile, 2023
  • [2]Implementation of synthetic scenarios for the study of the ambient noise tomography technique, Master Thesis and Memoria de pregrado, Universidad de Chile, 2017
  • [3]Técnicas de aplicaciones de separación de señales aplicadas en imágenes hiper espectrales, Memoria de pregrado, Universidad de Chile, 2016