NeuralPDE.jl

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Represent integral by a neural network

1

From the conversation here https://github.com/SciML/NeuralPDE.jl/issues/390#issuecomment-921892269 We should ammortize the integral cost. I.e., if we integrate from (0,x), then the next point is at (0,y), we really only need to solve...

killah-t-cell

https://arxiv.org/pdf/2104.10013.pdf - [ ] GPU - [ ] multi-GPU - [ ] MPI

KirillZubov

Adaptive activation function

6

https://arxiv.org/abs/1906.01170

KirillZubov

Time-Dependent PDE and RNN

2

https://arxiv.org/abs/2009.03892

KirillZubov

https://arxiv.org/abs/2102.11830

finmod

Add examples of 3D+ plots and analysis to NeuralPDE documentation

4

I had a generally positive experience working with higher dimensional PDEs, but I struggled to figure out how to analyze the results of these 3D+ PDEs effectively. I think it...

killah-t-cell

New regularization schemes for improving PINN convergence

1

https://proceedings.neurips.cc/paper/2021/file/df438e5206f31600e6ae4af72f2725f1-Paper.pdf

ChrisRackauckas

It's never a good idea, so it's bad form. We shouldn't show people bad form and then tell them to not do it in issues.

ChrisRackauckas

Neural Tangent Kernel Adaptive Loss

6

Implementing the Neural Tangent Kernel adaptive loss method proposed in the "When and Why PINNs Fail to Train: A Neural Tangent Kernel Perspective" [paper](https://arxiv.org/pdf/2007.14527.pdf) by Sifan Wang, Xinling Yu, Paris...

zoemcc

Inverse Dirichlet Adaptive Loss

1

Implementing the Inverse Dirichlet adaptive loss method proposed in this paper "Inverse Dirichlet weighting enables reliable training of physics informed neural networks" [paper](https://iopscience.iop.org/article/10.1088/2632-2153/ac3712/pdf) by Suryanarayana Maddu, Dominik Sturm, Christian L...

zoemcc