3 papers
cs.CV2026
A Proxy Consistency Loss for Grounded Fusion of Earth Observation and Location Encoders
Zhongying Wang, Kevin Lane, Levi Cai +2
Supervised learning with Earth observation inputs is often limited by the sparsity of high-quality labeled or in-situ measured data to use as training labels. With the abundance of…
cs.LG2025
Integrating Spatiotemporal Features in LSTM for Spatially Informed COVID-19 Hospitalization Forecasting
Zhongying Wang, Thoai D. Ngo, Hamidreza Zoraghein +2
The COVID-19 pandemic's severe impact highlighted the need for accurate and timely hospitalization forecasting to support effective healthcare planning. However, most forecasting m…
cs.LG2025
Performance and Generalizability Impacts of Incorporating Location Encoders into Deep Learning for Dynamic PM2.5 Estimation
Morteza Karimzadeh, Zhongying Wang, James L. Crooks
Deep learning has shown strong performance in geospatial prediction tasks, but the role of geolocation information in improving accuracy and generalizability remains underexamined.…