1 citations · 1 across the 7 of their papers we have counts for
4 papers · 2 filters
Nowcasting aerosol particle size distributions from PM2.5 with physics-regularized flow matching
Zhi-Song Liu, Jenni Köykkä, Wenqing Peng +3
The mass concentration of particles smaller than 2.5um (PM2.5) is cheap to measure and widely monitored, whereas the particle number size distribution (PSD) requires costly instrum…
Climate downscaling with likelihood functional flow matching
Zhi-Song Liu, Helmi Toropainen, Michael Boy +1
Decisions about heat, frost and flooding are made locally, yet reanalyses and climate models resolve tens of kilometres. Generative downscalers add kilometre-scale detail with unce…
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…
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…