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1. Nodes cannot directly fit multiplication and division operations; nodes can only use addition and subtraction.
2. When using the model, it is not possible to restrict the activation functions used…
hzy24 updated
1 month ago
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**Submitting author:** @thivinanandh (Thivin Anandh)
**Repository:** https://github.com/cmgcds/fastvpinns
**Branch with paper.md** (empty if default branch): joss_paper
**Version:** v1.0.1
**Editor:**…
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Great job! I wish that I had seen this earlier.
I would like to recommend
1. [When and why PINNs fail to train: A neural tangent kernel perspective](https://arxiv.org/abs/2007.14527)
2. [On the e…
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[Physics Informed Neural Networks by NVIDIA](https://docs.nvidia.com/deeplearning/modulus/user_guide/theory/recommended_practices.html#physics-informed-neural-networks) ... more generally, [Physics-In…
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I've noticed that in the PDE solving demo the ground truth solution for the PDE is used to evaluate the boundary condition loss and is thus used in the training process.
```
# boundar…
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Dear Authors,
I'm interesting in your paper "Physics-informed neural networks for inverse problems in nano-optics and metamaterials", in which you used DeepXDE lib. But I cannot find your code publ…
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## 🐛 Bug
## Minor Issues with rendering of Tutorials
1. https://deepchem.io/tutorials/physics-informed-neural-networks/ - Formula Not Rendering properly
2. https://deepchem.io/tutorials/int…
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I just want to know the mainly difference between static and dynamic in meshtype. Why the static is only used in 1D condition? The relative information in the paper "fPINNs: Fractional Physics-Inform…
TLDSZ updated
2 years ago
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Hi, I publish a paper about the PINN application for Li ion battery temp prediction.
Would you put my paper on your list?
G. Cho, M. Wang, Y. Kim, J. Kwon and W. Su, "A Physics-Informed Machine Le…
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I learned the hard bc of example diffusion_1d_exactBC, and your paper:PHYSICS-INFORMED NEURAL NETWORKS WITH HARD
CONSTRAINTS FOR INVERSE DESIGN∗, but I still can not apply hard bc to to other problem…