7 citations · 8 across the 5 of their papers we have counts for
6 papers
Domain-Adaptive Climate Downscaling Under Temporal Distribution Shift
Shuochen Wang, Nishant Yadav, Auroop R. Ganguly
Deep-learning-based climate downscaling aims to learn relationships from historical low-resolution (LR) and high-resolution (HR) climate data to generate HR climate projections. Ho…
climt-paraformer: Stable Emulation of Convective Parameterization using a Temporal Memory-aware Transformer
Shuochen Wang, Nishant Yadav, Joy Merwin Monteiro +1
Accurate representation of moist convective sub-grid-scale processes remains a major challenge in global climate models, as traditional parameterization schemes are both computatio…
Paraformer: Parameterization of Sub-grid Scale Processes Using Transformers
Shuochen Wang, Nishant Yadav, Auroop R. Ganguly
One of the major sources of uncertainty in the current generation of Global Climate Models (GCMs) is the representation of sub-grid scale physical processes. Over the years, a seri…
Deep Transfer Learning on Satellite Imagery Improves Air Quality Estimates in Developing Nations
Nishant Yadav, Meytar Sorek-Hamer, Michael Von Pohle +9
Urban air pollution is a public health challenge in low- and middle-income countries (LMICs). However, LMICs lack adequate air quality (AQ) monitoring infrastructure. A persistent…
Machine Learning for Robust Identification of Complex Nonlinear Dynamical Systems: Applications to Earth Systems Modeling
Nishant Yadav, Sai Ravela, Auroop R. Ganguly
Systems exhibiting nonlinear dynamics, including but not limited to chaos, are ubiquitous across Earth Sciences such as Meteorology, Hydrology, Climate and Ecology, as well as Biol…
Resilience of Urban Transport Network-of-Networks under Intense Flood Hazards Exacerbated by Targeted Attacks
Nishant Yadav, Samrat Chatterjee, Auroop R. Ganguly
Natural hazards including floods can trigger catastrophic failures in interdependent urban transport network-of-networks (NoNs). Population growth has enhanced transportation deman…