deeponet

There are 3 repositories under deeponet topic.

lululxvi / deepxde
A library for scientific machine learning and physics-informed learning
neural-network deep-learning scientific-machine-learning pinn multi-fidelity-data operator pytorch physics-informed-learning jax deeponet paddle pde tensorflow
Language:Python 2331
jdtoscano94 / Learning-Scientific_Machine_Learning_Residual_Based_Attention_PINNs_DeepONets
Physics Informed Machine Learning Tutorials (Pytorch and Jax)
deep-learning deeponet inverse-pinns inverse-problems jax machine-learning neural-network neural-networks physicsinformedneuralnetworks piins pytorch tutorial
Language:Jupyter Notebook 358
SciML / NeuralOperators.jl
DeepONets, (Fourier) Neural Operators, Physics-Informed Neural Operators, and more in Julia
julia fourier-transform gnn pde operator deep-learning partial-differential-equations automatic-differentiation deeponet differential-equations scientific-machine-learning fourier-neural-operator
Language:Julia 227
katiana22 / TL-DeepONet
Source code of 'Deep transfer operator learning for partial differential equations under conditional shift'.
deeponet hilbert-spaces multi-task-learning operator-learning partial-differential-equations physics-informed-learning regression transfer-learning
Language:Python 50
SciML / OperatorLearning.jl
No need to train, he's a smooth operator
julia physics-informed-ml neural-operator deeponet
Language:Julia 43
dtu-act / deeponet-acoustic-wave-prop
Code for training and inferring acoustic wave propagation in 3D
deeponet domain-decomposition operator-learning transfer-learning virtual-acoustics
Language:Python 19
katiana22 / surrogate-overparameterization
Source code of "On the influence of over-parameterization in manifold based surrogates and deep neural operators".
deeponet polynomial-chaos-expansions scientific-machine-learning surrogate-models
Language:Jupyter Notebook 2
liminghao0914 / CE7454-final
We implement a Multifidelity-DeepONet that leverages both high-fidelity CFD simulations and real-time, low-fidelity sensor data. We also proved that Multifidelity-DeepONet has better performance compare to all the others baseline methods in our experiments.
deeponet
Language:Jupyter Notebook 2
nimahsn / neuraloperators_jax
Neural Operators implemented with JAX and Equinox
deeponet jax neural-operator pde fno
Language:Python 1
nngabe / renonets
RenONet: Multiscale operator learning for complex social systems
deeponet graph-learning hyperbolic-geometry operator-learning
Language:Python 1