5 papers
Accurate and Robust Generative Approach for Overcoming Data Sparsity and Imbalance in Landslide Modeling with A Tabular Foundation Model
Kaixuan Shao, Gang Mei, Yinghan Wu +2
Landslide investigation relies on sufficient and well-balanced observational data influenced by geological, hydrological, and anthropogenic factors. Available landslide inventories…
Rainfall-induced Mass Movement as Self-organization Process
Zhengjing Ma, Gang Mei, Nengxiong Xu +2
Self-organizing processes shape Earth's surface, creating complex patterns from simple rules in most landforms. Rainfall-induced mass movements dramatically reshape landscapes thro…
Statistically Accurate and Robust Generative Prediction of Rock Discontinuities with A Tabular Foundation Model
Han Meng, Gang Mei, Hong Tian +2
Rock discontinuities critically govern the mechanical behavior and stability of rock masses. Their internal distributions remain largely unobservable and are typically inferred fro…
Tracking the Spatiotemporal Evolution of Landslide Scars Using a Vision Foundation Model: A Novel and Universal Framework
Meijun Zhou, Gang Mei, Zhengjing Ma +2
Tracking the spatiotemporal evolution of large-scale landslide scars is critical for understanding the evolution mechanisms and failure precursors, enabling effective early-warning…
Simple and Robust Forecasting of Spatiotemporally Correlated Small Earth Data with A Tabular Foundation Model
Yuting Yang, Gang Mei, Zhengjing Ma +2
Small Earth data are geoscience observations with limited short-term monitoring variability, providing sparse but meaningful measurements, typically exhibiting spatiotemporal corre…