23 citations · 31 across the 5 of their papers we have counts for
4 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…
Understanding the training of PINNs for unsteady flow past a plunging foil through the lens of input subdomain level loss function gradients
Rahul Sundar, Didier Lucor, Sunetra Sarkar
Recently immersed boundary method-inspired physics-informed neural networks (PINNs) including the moving boundary-enabled PINNs (MB-PINNs) have shown the ability to accurately reco…
Massive parallelization and performance enhancement of an immersed boundary method based unsteady flow solver
Rahul Sundar, Dipanjan Majumdar, Chhote Lal Shah +1
High-fidelity simulations of unsteady fluid flow are now possible with advancements in high-performance computing hardware and software frameworks. Since computational fluid dynami…