11 citations · 11 across the 3 of their papers we have counts for
3 papers · 1 filter
Continuous latent representations for modeling precipitation with deep learning
Gokul Radhakrishnan, Rahul Sundar, Nishant Parashar +3
The sparse and spatio-temporally discontinuous nature of precipitation data presents significant challenges for simulation and statistical processing for bias correction and downsc…
TAUDiff: Highly efficient kilometer-scale downscaling using generative diffusion models
Rahul Sundar, Yucong Hu, Nishant Parashar +2
Deterministic regression-based downscaling models for climate variables often suffer from spectral bias, which can be mitigated by generative models like diffusion models. To enabl…
A Multi-Scale Deep Learning Framework for Projecting Weather Extremes
Antoine Blanchard, Nishant Parashar, Boyko Dodov +2
Weather extremes are a major societal and economic hazard, claiming thousands of lives and causing billions of dollars in damage every year. Under climate change, their impact and…