# Any examples applying Physics Informed Neural Networks to ODEs?

**URL:** <https://discourse.julialang.org/t/any-examples-applying-physics-informed-neural-networks-to-odes/103512>\
**Category:** Machine Learning\
**Created:** [September 4, 2023, 3:15pm UTC](https://discourse.julialang.org/t/any-examples-applying-physics-informed-neural-networks-to-odes/103512 "2023-09-04T15:15:36Z")\
**Posts on this page:** 2\
**Page:** 1

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**Author:** ![affans](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/affans/32/11911_2.png) [@affans](https://discourse.julialang.org/u/affans)\
**Post date:** [September 4, 2023, 3:15pm UTC](https://discourse.julialang.org/t/any-examples-applying-physics-informed-neural-networks-to-odes/103512/1 "2023-09-04T15:15:36Z")

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I recently have been involved in PINNs and their applications. While I understand the mathematics of NNs, ODE solvers, PDEs, etc… I have very little experience in implementing them and in Julia especially. Does anyone have any examples/blog posts of applying PINNs to ODE systems? For what its worth, my research is in mathematical biology and the ODE systems I mostly work with are compartmental models (i.e. SIR/SEIR models).

An example of what I am looking for is this [LinkedIn video/post](https://www.linkedin.com/posts/mustafakaddoura_digitaltwin-neuralnetworks-deeplearning-activity-7091806122981945344-Z7IE?utm_source=share&utm_medium=member_desktop) by Mustafa K.

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**Author:** ![ChrisRackauckas](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/chrisrackauckas/32/77_2.png) [@ChrisRackauckas](https://discourse.julialang.org/u/ChrisRackauckas)\
**Post date:** [September 5, 2023, 2:04pm UTC](https://discourse.julialang.org/t/any-examples-applying-physics-informed-neural-networks-to-odes/103512/2 "2023-09-05T14:04:25Z")

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ODEs are just one dimensional PDEs. The documentation of NeuralPDE has quite a few examples of this:

[https://docs.sciml.ai/NeuralPDE/dev/tutorials/ode/](https://docs.sciml.ai/NeuralPDE/dev/tutorials/ode/)  
[https://docs.sciml.ai/NeuralPDE/dev/tutorials/param\_estim/](https://docs.sciml.ai/NeuralPDE/dev/tutorials/param_estim/)  
[https://docs.sciml.ai/NeuralPDE/dev/manual/ode/](https://docs.sciml.ai/NeuralPDE/dev/manual/ode/)

Note that we are changing the loss in these docs examples to make it more robust: [Docs modifications to use QuadratureTraining instead of GridTraining by sdesai1287 · Pull Request #729 · SciML/NeuralPDE.jl · GitHub](https://github.com/SciML/NeuralPDE.jl/pull/729)