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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:

A Geologically Constrained Variational Autoencoder for Mineral Prospectivity Mapping
Renguang Zuo, Zijing Luo, Yihui Xiong, et al.
Natural Resources Research (2022) Vol. 31, Iss. 3, pp. 1121-1133
Closed Access | Times Cited: 62

Showing 1-25 of 62 citing articles:

Graph Deep Learning Model for Mapping Mineral Prospectivity
Renguang Zuo, Ying Xu
Mathematical Geosciences (2022) Vol. 55, Iss. 1, pp. 1-21
Closed Access | Times Cited: 78
A Novel Scheme for Mapping of MVT-Type Pb–Zn Prospectivity: LightGBM, a Highly Efficient Gradient Boosting Decision Tree Machine Learning Algorithm
Mahsa Hajihosseinlou, Abbas Maghsoudi, Reza Ghezelbash
Natural Resources Research (2023) Vol. 32, Iss. 6, pp. 2417-2438
Closed Access | Times Cited: 56
Stacking: A novel data-driven ensemble machine learning strategy for prediction and mapping of Pb-Zn prospectivity in Varcheh district, west Iran
Mahsa Hajihosseinlou, Abbas Maghsoudi, Reza Ghezelbash
Expert Systems with Applications (2023) Vol. 237, pp. 121668-121668
Closed Access | Times Cited: 56
A New Generation of Artificial Intelligence Algorithms for Mineral Prospectivity Mapping
Renguang Zuo, Yihui Xiong, Ziye Wang, et al.
Natural Resources Research (2023) Vol. 32, Iss. 5, pp. 1859-1869
Closed Access | Times Cited: 45
Metallogenic prediction based on fractal theory and machine learning in Duobaoshan Area, Heilongjiang Province
Jun Chen, Zhonghai Zhao, Yuanjiang Yang, et al.
Ore Geology Reviews (2024) Vol. 168, pp. 106030-106030
Open Access | Times Cited: 32
Explainable artificial intelligence models for mineral prospectivity mapping
Renguang Zuo, Qiuming Cheng, Ying Xu, et al.
Science China Earth Sciences (2024) Vol. 67, Iss. 9, pp. 2864-2875
Closed Access | Times Cited: 20
An Interpretable Graph Attention Network for Mineral Prospectivity Mapping
Ying Xu, Renguang Zuo
Mathematical Geosciences (2023) Vol. 56, Iss. 2, pp. 169-190
Closed Access | Times Cited: 34
Mineral prospectivity mapping using attention-based convolutional neural network
Quanke Li, Guoxiong Chen, Lei Luo
Ore Geology Reviews (2023) Vol. 156, pp. 105381-105381
Open Access | Times Cited: 29
Metallogenic-Factor Variational Autoencoder for Geochemical Anomaly Detection by Ad-Hoc and Post-Hoc Interpretability Algorithms
Zijing Luo, Renguang Zuo, Yihui Xiong, et al.
Natural Resources Research (2023) Vol. 32, Iss. 3, pp. 835-853
Closed Access | Times Cited: 28
A physically constrained hybrid deep learning model to mine a geochemical data cube in support of mineral exploration
Renguang Zuo, Ying Xu
Computers & Geosciences (2023) Vol. 182, pp. 105490-105490
Closed Access | Times Cited: 26
Geologically Constrained Convolutional Neural Network for Mineral Prospectivity Mapping
Fanfan Yang, Renguang Zuo
Mathematical Geosciences (2024) Vol. 56, Iss. 8, pp. 1605-1628
Closed Access | Times Cited: 13
Dual-Branch Convolutional Neural Network and Its Post Hoc Interpretability for Mapping Mineral Prospectivity
Fanfan Yang, Renguang Zuo, Yihui Xiong, et al.
Mathematical Geosciences (2024) Vol. 56, Iss. 7, pp. 1487-1515
Closed Access | Times Cited: 11
Mineral Prospectivity Mapping Using Deep Self-Attention Model
Bojun Yin, Renguang Zuo, Siquan Sun
Natural Resources Research (2022) Vol. 32, Iss. 1, pp. 37-56
Closed Access | Times Cited: 34
3D convolutional neural Network-based 3D mineral prospectivity modeling for targeting concealed mineralization within Chating area, middle-lower Yangtze River metallogenic Belt, China
Xiaohui Li, Xue Chen, Yuheng Chen, et al.
Ore Geology Reviews (2023) Vol. 157, pp. 105444-105444
Open Access | Times Cited: 20
Recognition of mineralization-related anomaly patterns through an autoencoder neural network for mineral exploration targeting
Seyyed Ataollah Agha Seyyed Mirzabozorg, Maysam Abedi
Applied Geochemistry (2023) Vol. 158, pp. 105807-105807
Closed Access | Times Cited: 20
Workflow-Induced Uncertainty in Data-Driven Mineral Prospectivity Mapping
Steven E. Zhang, C J M Lawley, Julie E. Bourdeau, et al.
Natural Resources Research (2024) Vol. 33, Iss. 3, pp. 995-1023
Open Access | Times Cited: 8
Geologically-constrained GANomaly network for mineral prospectivity mapping through frequency domain training data
Hamid Sabbaghi, Seyed Hassan Tabatabaei, Nader Fathianpour
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 7
Enhancing training performance of convolutional neural network algorithm through an autoencoder-based unsupervised labeling framework for mineral exploration targeting
Seyyed Ataollah Agha Seyyed Mirzabozorg, Maysam Abedi, Mahyar Yousefi
Geochemistry (2024), pp. 126197-126197
Closed Access | Times Cited: 7
Artificial intelligence for mineral exploration: A review and perspectives on future directions from data science
Fanfan Yang, Renguang Zuo, Oliver P. Kreuzer
Earth-Science Reviews (2024), pp. 104941-104941
Closed Access | Times Cited: 7
Geochemical anomaly identification and uncertainty quantification using a Bayesian convolutional neural network model
Dazheng Huang, Renguang Zuo, Jian Wang
Applied Geochemistry (2022) Vol. 146, pp. 105450-105450
Closed Access | Times Cited: 27
An interpretable attention branch convolutional neural network for identifying geochemical anomalies related to mineralization
Fanfan Yang, Renguang Zuo, Yihui Xiong, et al.
Journal of Geochemical Exploration (2023) Vol. 252, pp. 107274-107274
Closed Access | Times Cited: 14
Incorporating Geological Knowledge into Deep Learning to Enhance Geochemical Anomaly Identification Related to Mineralization and Interpretability
Chunjie Zhang, Renguang Zuo
Mathematical Geosciences (2024) Vol. 56, Iss. 6, pp. 1233-1254
Closed Access | Times Cited: 6
Mineral prospectivity mapping using knowledge embedding and explainable ensemble learning: A case study of the Keeryin ore concentration in Sichuan, China
Shitao Yin, Nan Li, Keyan Xiao, et al.
Ore Geology Reviews (2024) Vol. 167, pp. 106017-106017
Open Access | Times Cited: 5
Data generation for exploration geochemistry: Past, present and future
Julie E. Bourdeau, Steven E. Zhang, Glen T. Nwaila, et al.
Applied Geochemistry (2024) Vol. 172, pp. 106124-106124
Open Access | Times Cited: 5
Geologically constrained unsupervised dual-branch deep learning algorithm for geochemical anomalies identification
Ying Xu, Luyi Shi, Renguang Zuo
Applied Geochemistry (2024) Vol. 174, pp. 106137-106137
Closed Access | Times Cited: 5
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