3 papers
physics.flu-dyn2025
Sequential learning based PINNs to overcome temporal domain complexities in unsteady flow past flapping wings
Rahul Sundar, Didier Lucor, Sunetra Sarkar
For a data-driven and physics combined modelling of unsteady flow systems with moving immersed boundaries, Sundar {\it et al.} introduced an immersed boundary-aware (IBA) framework…
cs.LG2024
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…
cs.LG2024
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…