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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:

Characterizing Uncertain Site-Specific Trend Function by Sparse Bayesian Learning
Jianye Ching, Kok‐Kwang Phoon
Journal of Engineering Mechanics (2017) Vol. 143, Iss. 7
Closed Access | Times Cited: 106

Showing 1-25 of 106 citing articles:

Scale of Fluctuation for Spatially Varying Soils: Estimation Methods and Values
Brigid Cami, Sina Javankhoshdel, Kok‐Kwang Phoon, et al.
ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems Part A Civil Engineering (2020) Vol. 6, Iss. 4
Closed Access | Times Cited: 148
A Review of Advanced Soil Moisture Monitoring Techniques for Slope Stability Assessment
Yongsheng Yao, J.Q. Fan, Jue Li
Water (2025) Vol. 17, Iss. 3, pp. 390-390
Open Access | Times Cited: 1
CPT-Based Probabilistic Characterization of Three-Dimensional Spatial Variability Using MLE
Te Xiao, Dian-Qing Li, Zi-Jun Cao, et al.
Journal of Geotechnical and Geoenvironmental Engineering (2018) Vol. 144, Iss. 5
Closed Access | Times Cited: 93
Statistical interpretation of spatially varying 2D geo-data from sparse measurements using Bayesian compressive sampling
Tengyuan Zhao, Yue Hu, Yu Wang
Engineering Geology (2018) Vol. 246, pp. 162-175
Closed Access | Times Cited: 90
The story of statistics in geotechnical engineering
Kok‐Kwang Phoon
Georisk Assessment and Management of Risk for Engineered Systems and Geohazards (2019) Vol. 14, Iss. 1, pp. 3-25
Closed Access | Times Cited: 87
Tunneling and deep excavations in spatially variable soil and rock masses: A short review
Wengang Zhang, Liang Han, Xin Gu, et al.
Underground Space (2020) Vol. 7, Iss. 3, pp. 380-407
Open Access | Times Cited: 85
Estimation of trend and random components of conditional random field using Gaussian process regression
Ikumasa Yoshida, Yukihisa Tomizawa, Yu Otake
Computers and Geotechnics (2021) Vol. 136, pp. 104179-104179
Open Access | Times Cited: 75
Non-parametric simulation of non-stationary non-gaussian 3D random field samples directly from sparse measurements using signal decomposition and Markov Chain Monte Carlo (MCMC) simulation
Tengyuan Zhao, Yu Wang
Reliability Engineering & System Safety (2020) Vol. 203, pp. 107087-107087
Closed Access | Times Cited: 71
Data-driven and physics-informed Bayesian learning of spatiotemporally varying consolidation settlement from sparse site investigation and settlement monitoring data
Hua-Ming Tian, Yu Wang
Computers and Geotechnics (2023) Vol. 157, pp. 105328-105328
Closed Access | Times Cited: 29
Interpolation of non-stationary geo-data using Kriging with sparse representation of covariance function
Cong Miao, Yu Wang
Computers and Geotechnics (2024) Vol. 169, pp. 106183-106183
Closed Access | Times Cited: 8
Interpolation of spatially varying but sparsely measured geo-data: A comparative study
Yu Wang, Oluwatosin Victor Akeju, Tengyuan Zhao
Engineering Geology (2017) Vol. 231, pp. 200-217
Closed Access | Times Cited: 86
Simulation of Random Fields with Trend from Sparse Measurements without Detrending
Yu Wang, Tengyuan Zhao, Yue Hu, et al.
Journal of Engineering Mechanics (2018) Vol. 145, Iss. 2
Closed Access | Times Cited: 78
Constructing a Site-Specific Multivariate Probability Distribution Using Sparse, Incomplete, and Spatially Variable (MUSIC-X) Data
Jianye Ching, Kok‐Kwang Phoon
Journal of Engineering Mechanics (2020) Vol. 146, Iss. 7
Closed Access | Times Cited: 68
Model selection in geological and geotechnical engineering in the face of uncertainty - Does a complex model always outperform a simple model?
C. Hsein Juang, Wenping Gong, James R. Martin, et al.
Engineering Geology (2018) Vol. 242, pp. 184-196
Closed Access | Times Cited: 63
Interpolation and stratification of multilayer soil property profile from sparse measurements using machine learning methods
Tengyuan Zhao, Yu Wang
Engineering Geology (2019) Vol. 265, pp. 105430-105430
Closed Access | Times Cited: 63
3D Probabilistic Site Characterization by Sparse Bayesian Learning
Jianye Ching, Wen‐Han Huang, Kok‐Kwang Phoon
Journal of Engineering Mechanics (2020) Vol. 146, Iss. 12
Closed Access | Times Cited: 51
Similarity quantification of soil parametric data and sites using confidence ellipses
Liang Han, Lin Wang, Xuanming Ding, et al.
Geoscience Frontiers (2021) Vol. 13, Iss. 1, pp. 101280-101280
Open Access | Times Cited: 51
Challenges in geotechnical design revealed by reliability assessment: Review and future perspectives
Yu Otake, Yusuke Honjo
SOILS AND FOUNDATIONS (2022) Vol. 62, Iss. 3, pp. 101129-101129
Open Access | Times Cited: 28
Bayesian updating of model parameters using adaptive Gaussian process regression and particle filter
Ikumasa Yoshida, Tomoka Nakamura, Siu‐Kui Au
Structural Safety (2023) Vol. 102, pp. 102328-102328
Closed Access | Times Cited: 19
Comparison of Data-Driven Site Characterization Methods through Benchmarking: Methodological and Application Aspects
Takayuki Shuku, Kok‐Kwang Phoon
ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems Part A Civil Engineering (2023) Vol. 9, Iss. 2
Closed Access | Times Cited: 16
Similarity quantification of soil spatial variability between two cross-sections using auto-correlation functions
Yue Hu, Yu Wang, Kok‐Kwang Phoon, et al.
Engineering Geology (2024) Vol. 331, pp. 107445-107445
Closed Access | Times Cited: 7
Dictionary Learning of Spatial Variability at a Specific Site Using Data from Other Sites
Zheng Guan, Yu Wang, Kok‐Kwang Phoon
Journal of Geotechnical and Geoenvironmental Engineering (2024) Vol. 150, Iss. 9
Closed Access | Times Cited: 5
Artificial neural network to characterize spatially varying quantity through random field approach
Pratyush Kumar
Neural Computing and Applications (2025)
Closed Access
Exploring High-Order Multivariate Geotechnical Features Using the Minimum Information Dependence Model
Taiga Saito, Yu Otake, Stephen Wu, et al.
Geodata and AI. (2025), pp. 100009-100009
Open Access
AI-powered NUN-SEDFN framework for addressing sparse data challenges in geotechnical parameter prediction
Z. Z. Wang, Rui Gao, Xiuren Hu
Advanced Engineering Informatics (2025) Vol. 65, pp. 103226-103226
Closed Access
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