63 citations as recorded by crossref.

1. Markov chain Monte Carlo for seismic facies classification D. Grana et al. https://doi.org/10.1190/geo2022-0442.1
2. Analysis and generation of the fibrosis textures based on histology data of the human hearts with non-ischemic cardiomyopathy A. Okenov et al. https://doi.org/10.1088/1361-6560/ade6bb
3. Training Image Optimization Method Based on Convolutional Neural Network and Its Application in Discrete Fracture Network Model Selection S. Yu et al. https://doi.org/10.2113/2021/4963324
4. Near-optimal, path-level parallelization for sequential geostatistical simulation M. Gravey & L. Rasera https://doi.org/10.1016/j.cageo.2026.106217
5. A review of geostatistical simulation models applied to satellite remote sensing: Methods and applications F. Zakeri & G. Mariethoz https://doi.org/10.1016/j.rse.2021.112381
6. Reconstruction of High-Resolution 3D GPR Data from 2D Profiles: A Multiple-Point Statistical Approach C. Zhang et al. https://doi.org/10.3390/rs16122084
7. 基于多尺度特征融合和深度可分离卷积的生成对抗网络地质建模方法 . Liu Xiaobo et al. https://doi.org/10.3799/dqkx.2026.009
8. Multiple-point geostatistics-based spatial downscaling of heavy rainfall fields W. Zou et al. https://doi.org/10.1016/j.jhydrol.2024.130899
9. Direct Sequential Simulation for spherical linear inverse problems M. Otzen et al. https://doi.org/10.1016/j.cageo.2021.105026
10. Geology-driven modeling: A new probabilistic approach for incorporating uncertain geological interpretations in 3D geological modeling R. Madsen et al. https://doi.org/10.1016/j.enggeo.2022.106833
11. Geostatistics-informed latent diffusion for conditional hydrogeological facies simulation under sparse hard-data constraints T. Xia et al. https://doi.org/10.1016/j.jhydrol.2026.136117
12. Multiple-point statistics and non-colocational soft data integration Ó. Jóhannsson & T. Hansen https://doi.org/10.1016/j.cageo.2022.105280
13. A Pattern Classification Distribution Method for Geostatistical Modeling Evaluation and Uncertainty Quantification C. Zuo et al. https://doi.org/10.3390/rs15112708
14. Integrating Multi-Point Geostatistics, Machine Learning, and Image Correlation for Characterizing Positional Errors in Remote-Sensing Images of High Spatial Resolution L. Xin et al. https://doi.org/10.3390/rs15194734
15. A parsimonious parametrization of the Direct Sampling algorithm for multiple-point statistical simulations P. Juda et al. https://doi.org/10.1016/j.acags.2022.100091
16. Adaptive direct sampling-based approach to ore grade modeling Z. Li et al. https://doi.org/10.1007/s12145-024-01297-4
17. A 3D Fold-Modeling Method Based on Multiple-Point Statistics and Long Short-Term Memory Networks X. Chen et al. https://doi.org/10.3390/app16094079
18. Estimating line contaminant sources in non-Gaussian groundwater conductivity fields using deep learning-based framework N. Zheng et al. https://doi.org/10.1016/j.jhydrol.2024.130727
19. A fast two part direct sampling method based on interpolation H. Bai et al. https://doi.org/10.1016/j.cageo.2023.105335
20. Stochastic reconstruction of heterogeneous microstructure combining sliced Wasserstein distance and gradient optimization Z. Ma et al. https://doi.org/10.1016/j.actamat.2024.120023
21. Reconstruction of Missing GPR Data Using Multiple-Point Statistical Simulation C. Zhang et al. https://doi.org/10.1109/TGRS.2024.3353482
22. Pore-scale simulations help in overcoming laboratory limitations with unconsolidated rock material: A multi-step reconstruction based on scanning electron and optical microscopy data D. Kulygin et al. https://doi.org/10.1016/j.advwatres.2024.104754
23. 3D multiple-point geostatistical simulation of joint subsurface redox and geological architectures R. Madsen et al. https://doi.org/10.5194/hess-25-2759-2021
24. Direct Sampling for Spatially Variable Extreme Event Generation in Resampling‐Based Stochastic Weather Generators J. Guevara et al. https://doi.org/10.1029/2022MS003542
25. Three-Dimensional Stratigraphic Modeling via Adaptive Search Strategy-Based Multiple-Point Geostatistical Simulation H. Fang et al. https://doi.org/10.1007/s11004-026-10316-7
26. Adaptive phase-retrieval stochastic reconstruction with correlation functions: Three-dimensional images from two-dimensional cuts A. Cherkasov et al. https://doi.org/10.1103/PhysRevE.104.035304
27. Functional multiple-point simulation O. Ojo & M. Genton https://doi.org/10.1016/j.cageo.2024.105767
28. Towards effective information content assessment: Analytical derivation of information loss in the reconstruction of random fields with model uncertainty A. Cherkasov et al. https://doi.org/10.1016/j.physa.2023.129400
29. Choosing between Gaussian and MPS simulation: the role of data information content—a case study using uncertain interpretation data points R. Madsen et al. https://doi.org/10.1007/s00477-020-01954-2
30. Estimation of Reservoir Fracture Properties from Seismic Data Using Markov Chain Monte Carlo Methods R. Feng et al. https://doi.org/10.1007/s11004-023-10129-y
31. A review of statistical methods for climate downscaling: the underexplored potential of geostatistical simulation S. Hadjipetrou https://doi.org/10.1007/s00704-026-06120-2
32. Generative Geomodelling: Deep Learning Versus Geostatistics with Insights from Sedimentary Systems S. Song et al. https://doi.org/10.1007/s11004-026-10273-1
33. Gap-Filling Sentinel-1 Offshore Wind Speed Image Time Series Using Multiple-Point Geostatistical Simulation and Reanalysis Data S. Hadjipetrou et al. https://doi.org/10.3390/rs15020409
34. DMCG: Diffusion-based multi-category generation network for characterizing heterogeneous hydrogeological structures D. Chen et al. https://doi.org/10.1016/j.jhydrol.2026.135501
35. A nearest neighbor multiple-point statistics method for fast geological modeling C. Zuo et al. https://doi.org/10.1016/j.cageo.2022.105208
36. Going submicron in the precise analysis of soil structure: A FIB-SEM imaging study at nanoscale K. Gerke et al. https://doi.org/10.1016/j.geoderma.2020.114739
37. Stochastic Facies Inversion with Prior Sampling by Conditional Generative Adversarial Networks Based on Training Image R. Feng et al. https://doi.org/10.1007/s11004-023-10119-0
38. AutoQS v1: automatic parametrization of QuickSampling based on training images analysis M. Gravey & G. Mariethoz https://doi.org/10.5194/gmd-16-5265-2023
39. Conditioning of multiple-point statistics simulations to indirect geophysical data S. Levy et al. https://doi.org/10.1016/j.cageo.2024.105581
40. Knowledge-based multiple point statistics for soil stratigraphy simulation X. Zhou et al. https://doi.org/10.1016/j.tust.2023.105475
41. SA‐RelayGANs: A Novel Framework for the Characterization of Complex Hydrological Structures Based on GANs and Self‐Attention Mechanism Z. Cui et al. https://doi.org/10.1029/2023WR035932
42. Stochastic (re)constructions of non-stationary material structures: Using ensemble averaged correlation functions and non-uniform phase distributions M. Karsanina & K. Gerke https://doi.org/10.1016/j.physa.2022.128417
43. Knowledge-Driven Adaptive Direct Sampling for Reconstructing Geochemical Fields Under Sampling Bias Y. Liu et al. https://doi.org/10.3390/ijgi15030111
44. Quantifying temporal variability and spatial heterogeneity in rainfall recharge thresholds in a montane karst environment A. Baker et al. https://doi.org/10.1016/j.jhydrol.2021.125965
45. Compressing soil structural information into parameterized correlation functions M. Karsanina et al. https://doi.org/10.1111/ejss.13025
46. Generating unrepresented proportions of geological facies using Generative Adversarial Networks A. Abdellatif et al. https://doi.org/10.1016/j.cageo.2022.105085
47. A variability aware GAN for improving spatial representativeness of discrete geobodies R. Koochak et al. https://doi.org/10.1016/j.cageo.2022.105188
48. Hydrogeological multiple-point statistics inversion by adaptive sequential Monte Carlo M. Amaya et al. https://doi.org/10.1016/j.advwatres.2022.104252
49. pyMPSLib: A robust and scalable open-source Python library for mutiple-point statistical simulation Q. Chen et al. https://doi.org/10.1007/s12145-023-01086-5
50. Super-resolution of digital elevation models by using multiple-point statistics and training image selection G. Hu et al. https://doi.org/10.1016/j.cageo.2024.105688
51. Semantic rule-guided three-dimensional reservoir modeling method using an improved multiple-point geostatistics simulation Q. Chen et al. https://doi.org/10.3389/feart.2026.1766398
52. Hierarchical 3D reconstruction algorithm of core image based on detailed and structural dictionaries Z. Ma et al. https://doi.org/10.1016/j.jgsce.2023.205029
53. Sulphur variations in annually layered stalagmites using benchtop micro-XRF H. Wang et al. https://doi.org/10.1016/j.sab.2022.106366
54. Pixel-MPS: Stochastic Embedding and Density-Based Clustering of Image Patterns for Pixel-Based Multiple-Point Geostatistical Simulation A. Asadi & S. Chatterjee https://doi.org/10.3390/geosciences14060162
55. Pattern-Based Multiple-point Geostatistics for 3D Automatic Geological Modeling of Borehole Data J. Guo et al. https://doi.org/10.1007/s11053-024-10405-6
56. Enhancing Aquifer Characterization With Position‐Encoded Hyperparameters: A Novel ES‐SIFG Approach M. Sun et al. https://doi.org/10.1029/2024WR038468
57. chessQS: An efficient tile-based gap-filling method for large and complex remote sensing images L. Gerber et al. https://doi.org/10.1016/j.ecoinf.2026.103666
58. A fast and flexible algorithm for microstructure reconstruction combining simulated annealing and deep learning Z. Ma et al. https://doi.org/10.1016/j.compgeo.2023.105755
59. A fast edge-based two-stage direct sampling method H. Bai & G. Mariethoz https://doi.org/10.1016/j.cageo.2021.104742
60. Stochastic Reconstruction of 3D Heterogeneous Microstructure Using a Column-Oriented Multiple-Point Statistics Program C. Zuo et al. https://doi.org/10.2113/2024/lithosphere_2023_233
61. Mapping high-resolution basal topography of West Antarctica from radar data using non-stationary multiple-point geostatistics (MPS-BedMappingV1) Z. Yin et al. https://doi.org/10.5194/gmd-15-1477-2022
62. Stationary Stokes solver for single-phase flow in porous media: A blastingly fast solution based on Algebraic Multigrid Method using GPU N. Evstigneev et al. https://doi.org/10.1016/j.advwatres.2022.104340
63. Identification of aquifer heterogeneity through inverse methods P. Ackerer et al. https://doi.org/10.5802/crgeos.162