CEDDAR Reproducibility Dataset and Trained Models (v1.0.1)
CEDDAR Reproducibility Dataset and Trained Models (v1.0.1)
This Zenodo record contains reproducibility assets for: CEDDAR: Controllable Ensemble Diffusion Downscaling for Atmospheric Rainfall (manuscript in preparation) Included: - Data_DiffMod_small: A small pre-processed example dataset used for reproducibility testing. This dataset allows execution of the 01_small_test and 02_reduced_run examples in the public CEDDAR repository. - B0.pth.tar: Baseline diffusion model weights. - B1_GSDF_RGBCE.pth.tar: Final trained model weights used in the manuscript. These assets correspond to CEDDAR GitHub release v1.0.1:https://github.com/TheaQG/CEDDAR The code archive is available separately at:https://doi.org/10.5281/zenodo.18643187
Climate Downscaling, Generative Modeling, Diffusion Models, Atmospheric Modeling, Probabilistic Downscaling, Precipitation Modeling
Climate Downscaling, Generative Modeling, Diffusion Models, Atmospheric Modeling, Probabilistic Downscaling, Precipitation Modeling
selected citations These citations are derived from selected sources.This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).0 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Average influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Average
Citations provided by BIP!Popularity provided by BIP!