206 citations · 227 across the 5 of their papers we have counts for
5 papers
Zero-Shot Uncertainty Quantification using Diffusion Probabilistic Models
Dule Shu, Amir Barati Farimani
The success of diffusion probabilistic models in generative tasks, such as text-to-image generation, has motivated the exploration of their application to regression problems commo…
Inpainting Computational Fluid Dynamics with Deep Learning
Dule Shu, Wilson Zhen, Zijie Li +1
Fluid data completion is a research problem with high potential benefit for both experimental and computational fluid dynamics. An effective fluid data completion method reduces th…
Latent Neural PDE Solver: a reduced-order modelling framework for partial differential equations
Zijie Li, Saurabh Patil, Francis Ogoke +5
Neural networks have shown promising potential in accelerating the numerical simulation of systems governed by partial differential equations (PDEs). Different from many existing n…
Scalable Transformer for PDE Surrogate Modeling
Zijie Li, Dule Shu, Amir Barati Farimani
Transformer has shown state-of-the-art performance on various applications and has recently emerged as a promising tool for surrogate modeling of partial differential equations (PD…
A Physics-informed Diffusion Model for High-fidelity Flow Field Reconstruction
Dule Shu, Zijie Li, Amir Barati Farimani
Machine learning models are gaining increasing popularity in the domain of fluid dynamics for their potential to accelerate the production of high-fidelity computational fluid dyna…