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Found 5 papers, 3 papers with code
A novel Fourier neural operator framework for classification of multi-sized images: Application to three dimensional digital porous media
First, we show that this approach is only effective for porous media with fixed sizes, whereas it fails for porous media of varying sizes.
Physics-informed PointNet: On how many irregular geometries can it solve an inverse problem simultaneously? Application to linear elasticity
In this article, we demonstrate that PIPN predicts the solution of desired partial differential equations over a few hundred domains simultaneously, while it only uses sparse labeled data.
ChatGPT for Programming Numerical Methods
Specifically, we examine the capability of GhatGPT for generating codes for numerical algorithms in different programming languages, for debugging and improving written codes by users, for completing missed parts of numerical codes, rewriting available codes in other programming languages, and for parallelizing serial codes.
Point-Cloud Deep Learning of Porous Media for Permeability Prediction
We compare our deep learning strategy with a convolutional neural network from various perspectives, specifically for maximum possible batch size.
A Point-Cloud Deep Learning Framework for Prediction of Fluid Flow Fields on Irregular Geometries
Grid vertices in a computational fluid dynamics (CFD) domain are viewed as point clouds and used as inputs to a neural network based on the PointNet architecture, which learns an end-to-end mapping between spatial positions and CFD quantities.
