no code implementations • 8 Aug 2024 • 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 commonly encountered in scientific computing and various other domains.
no code implementations • 27 Feb 2024 • Dule Shu, Wilson Zhen, Zijie Li, Amir Barati Farimani
Fluid data completion is a research problem with high potential benefit for both experimental and computational fluid dynamics.
no code implementations • 27 Feb 2024 • Zijie Li, Saurabh Patil, Francis Ogoke, Dule Shu, Wilson Zhen, Michael Schneier, John R. Buchanan, Jr., Amir Barati Farimani
Neural networks have shown promising potential in accelerating the numerical simulation of systems governed by partial differential equations (PDEs).
1 code implementation • NeurIPS 2023 • Zijie Li, Dule Shu, Amir Barati Farimani
These sub-functions are then evaluated and used to compute the instance-based kernel with an axial factorized scheme.
1 code implementation • 26 Nov 2022 • 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 dynamics data.