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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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This issue is to document our overal goals, ideas, and related publications. I'll keep the top of the issue as a clean summarry of the discussion in this thread.
## Goal of the Hackathon
Our goa…
EiffL updated
2 years ago
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# Description
Current challenges in using Neural Operators are: irregular meshes, multiple inputs, multiple inputs on different meshes, or multi-scale problems. [1] The Attention mechanism is promi…
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Hello, sorry i would have liked to comment in your blog but its not possible.
i have read the blog's page about weather prediction (very well written) and i was wondering if you think it could be p…
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The README states:
>The utility provided by this package is the function optfuns which returns three functions and p0, a vectorized version of pars.
This is now covered by `Flux.destructure`, w…
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Looking at the tutorials, the ordering looks a bit random. Perhaps we should reorder the tutorials, roughly in order from least to most advanced, to make it easier to understand them? I'd suggest some…
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# What is modulus?
From its official website, NVIDIA Modulus is `a neural network framework` that blends the power of `physics` (in the form of governing partial differential equations (PDEs)) with…
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**Submitting author:** @homerjed (Jed Homer)
**Repository:** https://github.com/homerjed/sbiax
**Branch with paper.md** (empty if default branch):
**Version:** 0.0.9
**Editor:** Pending
**Reviewers:*…
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@ChrisRackauckas have you seen this work by Ricky already?
https://arxiv.org/abs/2009.09457
**"Hey, that's not an ODE": Faster ODE Adjoints with 12 Lines of Code**
Patrick Kidger, Ricky T. Q. C…
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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…