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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

pynoddy 1.0: an experimental platform for automated 3-D kinematic and potential field modelling
Florian Wellmann, Samuel T. Thiele, Mark Lindsay, et al.
Geoscientific model development (2016) Vol. 9, Iss. 3, pp. 1019-1035
Open Access | Times Cited: 39

Showing 1-25 of 39 citing articles:

3-D Structural geological models: Concepts, methods, and uncertainties
Florian Wellmann, Guillaume Caumon
Advances in geophysics (2018), pp. 1-121
Open Access | Times Cited: 270
GemPy 1.0: open-source stochastic geological modeling and inversion
Miguel de la Varga, Alexander Schaaf, Florian Wellmann
Geoscientific model development (2019) Vol. 12, Iss. 1, pp. 1-32
Open Access | Times Cited: 155
The topology of geology 1: Topological analysis
Samuel T. Thiele, Mark Jessell, Mark Lindsay, et al.
Journal of Structural Geology (2016) Vol. 91, pp. 27-38
Closed Access | Times Cited: 132
Monte Carlo simulation for uncertainty estimation on structural data in implicit 3-D geological modeling, a guide for disturbance distribution selection and parameterization
Evren Pakyuz-Charrier, Mark Lindsay, Vitaliy Ogarko, et al.
Solid Earth (2018) Vol. 9, Iss. 2, pp. 385-402
Open Access | Times Cited: 104
Uncertainty estimation for a geological model of the Sandstone greenstone belt, Western Australia – insights from integrated geological and geophysical inversion in a Bayesian inference framework
Florian Wellmann, Miguel de la Varga, Ruth Murdie, et al.
Geological Society London Special Publications (2017) Vol. 453, Iss. 1, pp. 41-56
Open Access | Times Cited: 97
A Segmentation Approach for Stochastic Geological Modeling Using Hidden Markov Random Fields
Hui Wang, Florian Wellmann, Li Zhao, et al.
Mathematical Geosciences (2016) Vol. 49, Iss. 2, pp. 145-177
Closed Access | Times Cited: 87
A role for virtual outcrop models in blended learning – improved 3D thinking and positive perceptions of learning
Clare E. Bond, Adam J. Cawood
Geoscience Communication (2021) Vol. 4, Iss. 2, pp. 233-244
Open Access | Times Cited: 81
3D geological structure inversion from Noddy-generated magnetic data using deep learning methods
Jiateng Guo, Yunqiang Li, Mark Jessell, et al.
Computers & Geosciences (2021) Vol. 149, pp. 104701-104701
Closed Access | Times Cited: 67
The topology of geology 2: Topological uncertainty
Samuel T. Thiele, Mark Jessell, Mark Lindsay, et al.
Journal of Structural Geology (2016) Vol. 91, pp. 74-87
Closed Access | Times Cited: 66
Into the Noddyverse: a massive data store of 3D geological models for machine learning and inversion applications
Mark Jessell, Jiateng Guo, Yunqiang Li, et al.
Earth system science data (2022) Vol. 14, Iss. 1, pp. 381-392
Open Access | Times Cited: 36
Structural data constraints for implicit modeling of folds
Lachlan Grose, Gautier Laurent, Laurent Aillères, et al.
Journal of Structural Geology (2017) Vol. 104, pp. 80-92
Open Access | Times Cited: 59
Inversion of Structural Geology Data for Fold Geometry
Lachlan Grose, Gautier Laurent, Laurent Aillères, et al.
Journal of Geophysical Research Solid Earth (2018) Vol. 123, Iss. 8, pp. 6318-6333
Open Access | Times Cited: 59
Topological analysis in Monte Carlo simulation for uncertainty propagation
Evren Pakyuz-Charrier, Mark Jessell, Jérémie Giraud, et al.
Solid Earth (2019) Vol. 10, Iss. 5, pp. 1663-1684
Open Access | Times Cited: 48
A parametric fault displacement model to introduce kinematic control into modeling faults from sparse data
Gabriel Godefroy, Guillaume Caumon, Mary Ford, et al.
Interpretation (2017) Vol. 6, Iss. 2, pp. B1-B13
Open Access | Times Cited: 42
Integrated framework for geological modeling: integration of data, knowledge, and methods
Hong Li, Bo Wan, Deping Chu, et al.
Bulletin of Engineering Geology and the Environment (2024) Vol. 83, Iss. 8
Closed Access | Times Cited: 4
Estimating uncertainties in 3-D models of complex fold-and-thrust belts: A case study of the Eastern Alps triangle zone
Sofia Brisson, Florian Wellmann, Nils Chudalla, et al.
Applied Computing and Geosciences (2023) Vol. 18, pp. 100115-100115
Open Access | Times Cited: 10
Contrastive learning in building vision-language models for subsurface geoscience
Anatoly Aseev, Jing Huang, Priya Mishra
The Leading Edge (2025) Vol. 44, Iss. 2, pp. 80-95
Closed Access
Combining 3‐D Probabilistic Kinematic Modeling With Thermal Resetting Measurements: An Approach to Reduce Uncertainty in Exhumation Histories
Sofia Brisson, Denise Degen, David M. Nathan, et al.
Geochemistry Geophysics Geosystems (2025) Vol. 26, Iss. 3
Open Access
Two-Dimensional Stochastic Structural Geomodeling with Deep Generative Adversarial Networks
Charlie Garayt, Nicolas Desassis, Samy Blusseau, et al.
Mathematical Geosciences (2025)
Open Access
Constraining stochastic 3-D structural geological models with topology information using approximate Bayesian computation in GemPy 2.1
Alexander Schaaf, Miguel de la Varga, Florian Wellmann, et al.
Geoscientific model development (2021) Vol. 14, Iss. 6, pp. 3899-3913
Open Access | Times Cited: 20
Blockworlds 0.1.0: a demonstration of anti-aliased geophysics for probabilistic inversions of implicit and kinematic geological models
R. Scalzo, Mark Lindsay, Mark Jessell, et al.
Geoscientific model development (2022) Vol. 15, Iss. 9, pp. 3641-3662
Open Access | Times Cited: 13
Stochastic Inversion of Gravity Data Accounting for Structural Uncertainty
Noah D. Athens, Jef Caers
Mathematical Geosciences (2021) Vol. 54, Iss. 2, pp. 413-436
Closed Access | Times Cited: 18
Gravity inversion for geothermal exploration with uncertainty quantification
Noah D. Athens, Jef Caers
Geothermics (2021) Vol. 97, pp. 102230-102230
Closed Access | Times Cited: 13
Uncertainty Visualisation of a 3D Geological Geometry Model and Its Application in GIS-Based Mineral Resource Assessment: A Case Study in Huayuan District, Northwestern Hunan Province, China
Nan Li, Cangbai Li, Wenkai Chu, et al.
Journal of Earth Science (2021) Vol. 32, Iss. 2, pp. 358-369
Closed Access | Times Cited: 12
An automatic geological 3D cross-section generator: Geopropy, an open-source library
Ashkan Hassanzadeh, Enric Vázquez‐Suñé, Mercé Corbella, et al.
Environmental Modelling & Software (2022) Vol. 149, pp. 105309-105309
Open Access | Times Cited: 9
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