Physics Informed Neural Networks (PINNs) for Solving System of ODEs - A Beginner's Tutorial

[@elastropy]

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[@zhaokun-l8d]

Excellent video for learning PINNs solving odes

[@NDDAvid123]

Excellent video for learning PINNs

[@elastropy]

Hi @NDDAvid123, Thank you! I’m glad you found the video helpful for learning PINNs. Feel free to spread the word, and stay tuned for more content on this topic!

[@MOTIVAO]

Great videos on PINNS, keep up the great work

[@elastropy]

Hi @MOTIVAO, Thank you so much! I’m really glad you’re enjoying the videos on PINNs. Your support means a lot, and I’ll definitely keep working on more content. Stay tuned for future tutorials!

[@lysaait1711]

Thanks

[@elastropy]

Hi @lysaait1711, you are welcome.

[@azeemishaq8240]

Please solve coupled nonlinear system of odes using pinns

[@656-aiml2]

Can you also provide the same for the inverse PINNs implementation with learnable parameter.

[@amanaliali7050]

Please make videos on fuzzy logic and neural network. Your content is really helpful.

[@rakesh-do1hw]

It's the great video on PINNS. I will really appreciate if you can share the jupyter notebook used as it will help me in practicing code myself, further strengthening my concept on punns. THANKS IN ADVANCE...

[@elastropy]

Hi @rakesh-do1hw, thank you for the kind words! 😊 I’m glad you enjoyed the video. Our source codes are completely free of cost. You can download the Jupyter notebook and source code by following the instructions given in the below link. To download the source codes, you’ll need to complete a small quiz-don’t worry, all the answers can be found in the video! Happy Learning. Link - www.elastropy.com/more/unlock-free-source-codes

[@patelpavan5479]

What is means here 0:1 and 1:2 in x=output [:,0:1] , y=output[:,1:2]

[@elastropy]

Hi @patelpavan5479, could you please send me the time stamp in the video, at which you saw these?? Also, could you please elaborate your doubt?

[@patelpavan5479]

​@@elastropy15:20

[@elastropy]

Hi @patelpavan5479, thanks for the timestamp. I did it this way to preserve the 2D array shape for consistency in tensor operations.

[@patelpavan5479]

@@elastropy ok

[@dilharawickramasinghe7121]

Great explanation! Could you share the code please?

[@THEKHURRAM100]

Please share notebook link

[@elastropy]

Hi @THEKHURRAM100, our source codes are completely free of cost. You can download the Jupyter notebook and source code by following the instructions given in the below link. To download the source codes, you’ll need to complete a small quiz-don’t worry, all the answers can be found in the video! Happy Learning. Link - www.elastropy.com/more/unlock-free-source-codes

[@p.zh.6132]

Thanks for sharing, can u tell us how to solve ODEs with uncertain eigenvalues, for example, y'' + λ*y = 0 with BCs: y(0) = y(2π)=0?

[@elastropy]

Hi @p.zh.6132, Thank you for your comment! Solving y'' + λ*y = 0 with BCs: y(0) = y(2π)=0 (a Sturm-Liouville eigenvalue problem) using PINNs is indeed a complex problem, especially due to the presence of multiple eigenvalues. To address this, additional constraints such as orthogonality conditions are typically required to isolate specific eigenvalues or ensure the solution satisfies the physical properties of the problem. These constraints can be incorporated into the loss function alongside the governing equation and boundary conditions.

[@rituparnsingh6554]

Are we using Tensorflow1.x or 2.x for these codes? I am guessing its the former?

[@elastropy]

Hi @rituparnsingh6554, we use TensorFlow 2.x for these codes. If you install via pip install, it will automatically install TensorFlow 2.x by default. 😊

[@rajibali4643]

Please makenthis on SDE please

[@elastropy]

Hi @rajibali4643, did you mean Stochastic Differential Equations for SDE??