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# Convolutional neural networks for solving PDEs | Arthur Bauville
Writing an iterative multigrid PDE solver as a convolutional neural network
[https://abauville.github.io/blog/neural%20networks/202…
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We are having some difficulties solving two coupled multi-variate non-linear PDEs using Gridap.
We have two PDEs that we need to solve together in increments for the vector field `uh` and the scala…
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Hello, I was wondering if the code currently supports solving a BVP of the form $L(u) = v,$ where $L$ is some differential operator, $u(x,y), v(x,y) \in \mathbb{R}^2$ and $x$ and $y$ are scalar coordi…
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We should definitely organize the `examples` directory into subdirectories as this package becomes larger, but I am not sure if it makes sense to do so based on solver/mesh type the way Trixi.jl does.…
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Due to some issues with org-element or org-element caching that I'm having trouble reproducing, latex previews sometimes fail in indirect Org buffers. I'm keeping an eye for a deterministic, reproduc…
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Instead of embedding the simplicial complex, we can implement everything with the intrinsic manifold view.
This means that the vertices no longer have coordinates, but all the geometry information st…
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Dear @yihang-gao
Thank you for sharing these amazing codes. Is this structure capable of solving stochastic coupled PDEs? (I mean PDEs that have some parameters that are not deterministic and they h…
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I would like to know whether the problems of this paper were solved via deepxde? Beacause you mention this paper as an application of deepxde on your deepxde documentation. But no code is available. I…
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Hello,
You write that this repository is the AD for the paper: Physics-informed Quantum Deep Neural Network for Solving PDEs. I cannot find the paper. Are you still writing it? Do you have a prepri…
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Hi,
I'm currently trying to use DeepXDE to solve the Black-Scholes equation for one space dimension and then higher ones after that. It is as follows:
**Black-Scholes Equation**
$$\frac{\partial …