PaddleScience is SDK and library for developing AI-driven scientific computing applications based on PaddlePaddle.
-
Updated
Oct 9, 2024 - Python
PaddleScience is SDK and library for developing AI-driven scientific computing applications based on PaddlePaddle.
Source code of 'Deep transfer operator learning for partial differential equations under conditional shift'.
Datasets and code for results presented in the BOON paper
Hyperbolic Learning Rate Scheduler
Official repo for separable operator networks -- extreme-scale operator learning for parametric PDEs.
CODES (Coupled ODE Surrogates) aims to make surrogates for coupled ODE systems comparable and to aid in learning about their learning behaviour.
Code for training and inferring acoustic wave propagation in 3D
Graph Feedforward Networks: a resolution-invariant generalisation of feedforward networks for graphical data, applied to model order reduction
Nonlinear model reduction for operator learning
Project Portfolio
Code for the paper ``Error Bounds for Learning with Vector-Valued Random Features''
Code for the paper "The Random Feature Model for Input-Output Maps between Banach Spaces"
An extension of Fourier Neural Operator to finite-dimensional input and/or output spaces.
RenONet: Multiscale operator learning for complex social systems
Code required to reproduce results presented in "Probabilistic Operator Learning for Climate Model Parameterisation"
Fokker Planck based Data Assimilation method using Fourier Neural Operators as integrator
Add a description, image, and links to the operator-learning topic page so that developers can more easily learn about it.
To associate your repository with the operator-learning topic, visit your repo's landing page and select "manage topics."