4 papers
TopoFlow: Topography-aware Pollutant Flow Learning for High-Resolution Air Quality Prediction
Ammar Kheder, Helmi Toropainen, Wenqing Peng +4
We propose TopoFlow (Topography-aware pollutant Flow learning), a physics-guided neural network for efficient, high-resolution air quality prediction. To explicitly embed physical…
Inverse Neural Operator for ODE Parameter Optimization
Zhi-Song Liu, Wenqing Peng, Helmi Toropainen +5
We propose the Inverse Neural Operator (INO), a two-stage framework for recovering hidden ODE parameters from sparse, partial observations. In Stage 1, a Conditional Fourier Neural…
Cross-Resolution Attention Network for High-Resolution PM2.5 Prediction
Ammar Kheder, Helmi Toropainen, Wenqing Peng +3
Vision Transformers have achieved remarkable success in spatio-temporal prediction, but their scalability remains limited for ultra-high-resolution, continent-scale domains require…
Deep Spatio-Temporal Neural Network for Air Quality Reanalysis
Ammar Kheder, Benjamin Foreback, Lili Wang +2
Air quality prediction is key to mitigating health impacts and guiding decisions, yet existing models tend to focus on temporal trends while overlooking spatial generalization. We…