Kexin Yin

From Imperfect Geotechnical Data to Accurate Prediction: Rockburst Classification Using the Pretrained Transformer TabPFN Model

Predicting underground mining rockbursts remains challenging because geotechnical data sets are often small, sparse, incomplete, and noisy, resulting from inconsistent testing standards, high acquisition costs, measurement errors, and geological variability. Consequently, traditional machine learning (ML) models fr...