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Hi Lu @lululxvi ,
First of all, thanks for providing such a powerful tool set so that we can adopt it to simulate various physical problems.
For above issue, I've almost gone through all the rel…
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I am getting "TypeError: 'function' object is not subscriptable" after the model.compile line. I have included the error first and then my code follows. Thank you very much for any assistance.
> …
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I read your paper online about the deep learning library for differential equations and I tried using your DEEPXDE package to solve a simple 2D Laplace equation but the errors I am getting are not ver…
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I'm trying to model a the electrostatic potential in a 3D volume with 3 electrodes on the boundary. I would like to include the voltage of the electrodes as parameters to the model so that I can quic…
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Hello,
I am currently trying to implement the Helmholtz equation in 1D (evaluating an acoustical problem) given as:
![\dfrac{dp(x)^2}{dx^2} + k^2 p(x) = 0](https://render.githubusercontent.com/r…
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Hi,lulu
I want to identify the parameter q(x) in elliptic equation -du_xx + q(x)u =f, x\in [-1,1], where true solution u=sin(pi*x^2), q(x)=cos(x) is unknown. The following is the code: the train loss…
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I think the docs should have these sections:
1. Neural networks can be defined where the "activations" are nonlinear functions described by differential equations
2. Neural networks can be defined…
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Hi @lululxvi, thanks for the excellent library.
I am interested in creating a PDE to be learned by the neural network that depends on an input condition.
For instance, from example [ode_system.…
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I appreciate the author shares his code with us, faciliating our exploration for PINN. Recently I tried to use the DeepXDE to model the potential flow over cylinder, a brief introduction can be found …
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Hi.
First of all. DeepXDE is really great!
It is amazing that a neural net can solve PDEs.
I did some experiments and I encountered results that I don't understand. So I hope I can get some expla…