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20212025
most citedHeterogeneous Data Fusion Considering Spatial Correlations using Graph Convolutional Networks and its Application in Air Quality Prediction

7 citations · 9 across the 4 of their papers we have counts for

collaborators

5 papers

physics.geo-ph2025

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…

cs.CV2025

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…

cs.LG2025

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…

cs.LG2023★ 2 cited

Knowledge-infused Deep Learning Enables Interpretable Landslide Forecasting

Zhengjing Ma, Gang Mei

Forecasting how landslides will evolve over time or whether they will fail is a challenging task due to a variety of factors, both internal and external. Despite their considerable…

cs.LG2021★ 7 cited

Heterogeneous Data Fusion Considering Spatial Correlations using Graph Convolutional Networks and its Application in Air Quality Prediction

Zhengjing Ma, Gang Mei, Salvatore Cuomo +1

Heterogeneous data are commonly adopted as the inputs for some models that predict the future trends of some observations. Existing predictive models typically ignore the inconsist…