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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Updated
Oct 11, 2024 - Python
CODES (Coupled ODE Surrogates) aims to make surrogates for coupled ODE systems comparable and to aid in learning about their learning behaviour.
PaddleScience is SDK and library for developing AI-driven scientific computing applications based on PaddlePaddle.
Nonlinear model reduction for operator learning
Hyperbolic Learning Rate Scheduler
Official repo for separable operator networks -- extreme-scale operator learning for parametric PDEs.
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"
Project Portfolio
Code required to reproduce results presented in "Probabilistic Operator Learning for Climate Model Parameterisation"
Graph Feedforward Networks: a resolution-invariant generalisation of feedforward networks for graphical data, applied to model order reduction
Fokker Planck based Data Assimilation method using Fourier Neural Operators as integrator
An extension of Fourier Neural Operator to finite-dimensional input and/or output spaces.
Code for training and inferring acoustic wave propagation in 3D
RenONet: Multiscale operator learning for complex social systems
Source code of 'Deep transfer operator learning for partial differential equations under conditional shift'.
Datasets and code for results presented in the BOON paper
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