5 citations · 18 across the 10 of their papers we have counts for
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cs.LG2025
WildfireGenome: Interpretable Machine Learning Reveals Local Drivers of Wildfire Risk and Their Cross-County Variation
Chenyue Liu, Ali Mostafavi
Current wildfire risk assessments rely on coarse hazard maps and opaque machine learning models that optimize regional accuracy while sacrificing interpretability at the decision s…
cs.LG2023★ 1 cited
Decoding Urban-health Nexus: Interpretable Machine Learning Illuminates Cancer Prevalence based on Intertwined City Features
Chenyue Liu, Ali Mostafavi
This study investigates the interplay among social demographics, built environment characteristics, and environmental hazard exposure features in determining community level cancer…
cs.LG2022★ 1 cited
Graph Attention Networks Unveil Determinants of Intra- and Inter-city Health Disparity
Chenyue Liu, Chao Fan, Ali Mostafavi
Understanding the determinants underlying variations in urban health status is important for informing urban design and planning, as well as public health policies. Multiple hetero…