Examples implementing physics-informed neural networks (PINN) in Pytorch
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Pytorch_NN_example:
Linear and nonlinear regression examples with a neural network implemented in Pytorch.
An excellent detailed intro to neural networks with Pytorch: https://www.deeplearningwizard.com/deep_learning/practical_pytorch/pytorch_feedforward_neuralnetwork/
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Pytorch_PINN:
1d_advdif_PINN.py: Solve steady 1D advection-diffusion equation using PINN.
2d_diffusion_PINN.py: Solve steady 2D diffusion equation with a source term using PINN
stenosis_NS.py: Solve steady 2D Navier-Stokes equation in an idealized stenosis model using PINN. The data needed for the 2D stenosis model are located here:
https://github.com/amir-cardiolab/PINN-wss/tree/main/Data/2D-stenosis
Need to install visualization toolkint (vtk) libraries to read the input data:
conda activate pytorch
pip install vtk
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Inverse modeling using PINN:
See: https://github.com/amir-cardiolab/PINN-wss
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Useful seminars about PINNs:
Karniadakis (PINN overview):
https://www.youtube.com/watch?v=FQ0vsqU-K00&list=PLw74xLHy0_j8DXxAKb15DbgtNvUOeTPbZ&index=2&ab_channel=MSML2020Conference
Lu (solving PDEs with PINN):
https://www.youtube.com/watch?v=Wfgr1pMA9fY&list=PLw74xLHy0_j8DXxAKb15DbgtNvUOeTPbZ&index=4&t=1879s&ab_channel=MLPS-CombiningAIandMLwithPhysicsSciences
Karniadakis (PINN overview and various applications):
https://www.youtube.com/watch?v=7kCq2uQmQU4&list=PLw74xLHy0_j8DXxAKb15DbgtNvUOeTPbZ&index=27&t=3s&ab_channel=CambridgeUniversityPress-Academic
Raissi (inverse modeling with PINN; SECOND HALF OF THE TALK):
https://www.youtube.com/watch?v=iy4PIeW91_I&t=2363s&ab_channel=MLPS-CombiningAIandMLwithPhysicsSciences
Perdikaris (PINN overview and challenges):
https://www.youtube.com/watch?v=68MtA0L9ZAI&t=3327s&ab_channel=TexasA%26MInstituteofDataScience
Wang (superresolution with PINN):
https://www.youtube.com/watch?v=xMimSG4NBT0&t=1s&ab_channel=JianxunWang
Arzani (identifyng wall shear stress from sparse data with PINN):
https://www.youtube.com/watch?v=rK-Bb6-0svs&ab_channel=AmirhosseinArzani