Spatial+: A new cross-validation method to evaluate geospatial machine learning models. - Yanwen Wang 004; Mahdi Khodadadzadeh; Raúl Zurita-Milla (Int. J. Appl. Earth Obs. Geoinformation, 2023)

Assessing spatiotemporal bikeability using multi-source geospatial big data: A case study of Xiamen, China. - Shaoqing Dai; Wufan Zhao; Yanwen Wang 004; Xiao Huang 003; Zhidong Chen; Jinghan Lei; Alfred Stein; Peng Jia (Int. J. Appl. Earth Obs. Geoinformation, 2023)

On the use of adversarial validation for quantifying dissimilarity in geospatial machine learning prediction. - Yanwen Wang 004; Mahdi Khodadadzadeh; Raúl Zurita-Milla (CoRR, 2024)

Mapping Street Patterns with Network Science and Supervised Machine Learning. - Cai Wu; Yanwen Wang 004; Jiong Wang; Menno-Jan Kraak; Mingshu Wang (ISPRS Int. J. Geo Inf., 2024)

A dissimilarity-adaptive cross-validation method for evaluating geospatial machine learning predictions with clustered samples. - Yanwen Wang 004; Mahdi Khodadadzadeh; Raúl Zurita-Milla (Ecol. Informatics, 2025)