Datasets and code for results presented in the BOON paper
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Updated
Mar 2, 2023 - Jupyter Notebook
Datasets and code for results presented in the BOON paper
Source code of 'Deep transfer operator learning for partial differential equations under conditional shift'.
RenONet: Multiscale operator learning for complex social systems
Code for training and inferring acoustic wave propagation in 3D
An extension of Fourier Neural Operator to finite-dimensional input and/or output spaces.
Fokker Planck based Data Assimilation method using Fourier Neural Operators as integrator
Graph Feedforward Networks: a resolution-invariant generalisation of feedforward networks for graphical data, applied to model order reduction
Code required to reproduce results presented in "Probabilistic Operator Learning for Climate Model Parameterisation"
Project Portfolio
Code for the paper "The Random Feature Model for Input-Output Maps between Banach Spaces"
Code for the paper ``Error Bounds for Learning with Vector-Valued Random Features''
Official repo for separable operator networks -- extreme-scale operator learning for parametric PDEs.
Hyperbolic Learning Rate Scheduler
Nonlinear model reduction for operator learning
PaddleScience is SDK and library for developing AI-driven scientific computing applications based on PaddlePaddle.
CODES (Coupled ODE Surrogates) aims to make surrogates for coupled ODE systems comparable and to aid in learning about their learning behaviour.
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