A tabular foundation model generates realistic landslide data matching observed distributions and dependencies across 20 inventories, addressing sparsity and imbalance for improved susceptibility modeling.
Optimizing the predictive ability of machine learning methods for landslide susceptibility mapping using smote for lishui city in zhejiang province, china
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Accurate and Robust Generative Approach for Overcoming Data Sparsity and Imbalance in Landslide Modeling with A Tabular Foundation Model
A tabular foundation model generates realistic landslide data matching observed distributions and dependencies across 20 inventories, addressing sparsity and imbalance for improved susceptibility modeling.