PFD-BDCM is a diffusion-based structural causal model that represents dynamic spatio-temporal confounders via conditional autoregressive processes and functional data via basis expansions, with theoretical preservation of causal effects and empirical outperformance on synthetic and air-pollution dat
Persistent growth of anthropogenic nmvoc emissions in china during 1990-2017: Dynamics, speciation, and ozone formation potentials
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Partially Functional Dynamic Backdoor Diffusion-based Causal Model
PFD-BDCM is a diffusion-based structural causal model that represents dynamic spatio-temporal confounders via conditional autoregressive processes and functional data via basis expansions, with theoretical preservation of causal effects and empirical outperformance on synthetic and air-pollution dat