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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:

Joint modelling of landslide counts and sizes using spatial marked point processes with sub-asymptotic mark distributions
Rishikesh Yadav, Raphaël Huser, Thomas Opitz, et al.
Journal of the Royal Statistical Society Series C (Applied Statistics) (2023) Vol. 72, Iss. 5, pp. 1139-1161
Open Access | Times Cited: 13

Showing 13 citing articles:

On the use of explainable AI for susceptibility modeling: Examining the spatial pattern of SHAP values
Nan Wang, Hongyan Zhang, Ashok Dahal, et al.
Geoscience Frontiers (2024) Vol. 15, Iss. 4, pp. 101800-101800
Open Access | Times Cited: 24
Deep graphical regression for jointly moderate and extreme Australian wildfires
Daniela Cisneros, J. Ian Richards, Ashok Dahal, et al.
Spatial Statistics (2024) Vol. 59, pp. 100811-100811
Open Access | Times Cited: 13
Space-time modeling of landslide size by combining static, dynamic, and unobserved spatiotemporal factors
Zhice Fang, Yi Wang, C.J. van Westen, et al.
CATENA (2024) Vol. 240, pp. 107989-107989
Closed Access | Times Cited: 10
Landslide hazard spatiotemporal prediction based on data-driven models: Estimating where, when and how large landslide may be
Zhice Fang, Yi Wang, C.J. van Westen, et al.
International Journal of Applied Earth Observation and Geoinformation (2023) Vol. 126, pp. 103631-103631
Open Access | Times Cited: 18
At the Junction Between Deep Learning and Statistics of Extremes: Formalizing the Landslide Hazard Definition
Ashok Dahal, Raphaël Huser, Luigi Lombardo
Journal of Geophysical Research Machine Learning and Computation (2024) Vol. 1, Iss. 3
Open Access | Times Cited: 8
Towards physics-informed neural networks for landslide prediction
Ashok Dahal, Luigi Lombardo
Engineering Geology (2024), pp. 107852-107852
Open Access | Times Cited: 4
Approximate Bayesian Inference for High-Resolution Spatial Disaggregation Using Alternative Data Sources
Anis Pakrashi, Arnab Hazra, Sooraj M Raveendran, et al.
Journal of Agricultural Biological and Environmental Statistics (2025)
Closed Access
An ensemble neural network approach for space-time landslide predictive modelling
Jana P. Lim, Giorgio Santinelli, Ashok Dahal, et al.
EarthArXiv (California Digital Library) (2024)
Open Access | Times Cited: 3
An ensemble neural network approach for space–time landslide predictive modelling
Jana P. Lim, Giorgio Santinelli, Ashok Dahal, et al.
International Journal of Applied Earth Observation and Geoinformation (2024) Vol. 132, pp. 104037-104037
Open Access | Times Cited: 3
Pan‐European Landslide Risk Assessment: From Theory to Practice
Francesco Caleca, Luigi Lombardo, Stefan Steger, et al.
Reviews of Geophysics (2025) Vol. 63, Iss. 1
Open Access
Spatiotemporal joint analysis of PM2.5 and Ozone in California with INLA approach
Jianan Pan, Kunyang He, Kai Wang, et al.
Journal of Environmental Management (2024) Vol. 363, pp. 121294-121294
Closed Access | Times Cited: 2
Anthropogenic and meteorological effects on the counts and sizes of moderate and extreme wildfires
Elizabeth S. Lawler, Benjamin A. Shaby
Environmetrics (2024) Vol. 35, Iss. 7
Open Access
Distribution-agnostic landslide hazard modeling via Graph Transformers
Gabriele Belvederesi, Hakan Tanyaş, Aldo Lipani, et al.
Environmental Modelling & Software (2024) Vol. 183, pp. 106231-106231
Open Access
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