346 citations · 706 across the 5 of their papers we have counts for
5 papers
Learning Accurate Storm-Scale Evolution from Observations
Jaideep Pathak, Mohammad Shoaib Abbas, Peter Harrington +10
Accurate short-term prediction of clouds and precipitation is critical for severe weather warnings, aviation safety, and renewable energy operations. Forecasts at this timescale ar…
Transformers for Modeling Physical Systems
Nicholas Geneva, Nicholas Zabaras
Transformers are widely used in natural language processing due to their ability to model longer-term dependencies in text. Although these models achieve state-of-the-art performan…
Multi-fidelity Generative Deep Learning Turbulent Flows
Nicholas Geneva, Nicholas Zabaras
In computational fluid dynamics, there is an inevitable trade off between accuracy and computational cost. In this work, a novel multi-fidelity deep generative model is introduced…
Modeling the Dynamics of PDE Systems with Physics-Constrained Deep Auto-Regressive Networks
Nicholas Geneva, Nicholas Zabaras
In recent years, deep learning has proven to be a viable methodology for surrogate modeling and uncertainty quantification for a vast number of physical systems. However, in their…
Quantifying model form uncertainty in Reynolds-averaged turbulence models with Bayesian deep neural networks
Nicholas Geneva, Nicholas Zabaras
Data-driven methods for improving turbulence modeling in Reynolds-Averaged Navier-Stokes (RANS) simulations have gained significant interest in the computational fluid dynamics com…