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After the pre-alpha development we need to design a suitable tests facilities. The library is aimed to be a general approximation (interpolation) tool thus the range of applications is quite wide. Nev…
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I will give an overview of MEUMAPPS C++, an open-source framework for solving PDEs using the Fourier pseudospectral method that combines Kokkos with heFFTe (performance portable FFTs) and Sundials (pe…
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Hi, I am thinking of using VoronoiFVM.jl for solving a set of different PDEs governing the evolution of snow on the ground in 1D. In order to follow the ice-matrix in snow, it is usual to solve diffus…
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we're currently at v0.5.0, whatever the hell that means, and I'm interested in knowing what the plans are. I'm the one driving the dev, and I'm super 100% okay with that as numerical stuff is my game,…
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First of all, thank you for developing this package, it's a very instructive way to learn about function decomposition methods!
And I do like the way time dependent PDEs can be solved by extending …
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Hi all,
I am Balaje, a PhD student in Mathematics. Saw the project list for Gridap.jl for GSoC 2021. I am interested in the topic - [Gridap.jl data-driven applications via Flux.jl](https://github.…
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Approximations allow us to include model components that don't have autodiff-friendly implementations.
- A first test case will be approximating the local coupling term in a neural field model
- A…
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* [Link](https://arxiv.org/pdf/1904.07200.pdf)
* Title: A Discussion on Solving Partial Differential Equations using Neural Networks
* Keywords (optional):
* Authors (optional):
* Reason (o…
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These came up when I was randomly generating surfaces and intersecting them (and solving some PDEs along the way). There are (at least 4 cases).
## Case 1
```python
import bezier
import numpy …
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```python
import fipy as fp
nx = 20
ny = nx
dx = 1
dy = dx
mesh = fp.Grid2D(dx=dx, dy=dy, nx=nx, ny=ny)
phi = fp.CellVariable(mesh=mesh, value=0.)
eq = fp.TransientTerm() == fp.DiffusionTe…
guyer updated
4 years ago