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https://en.m.wikipedia.org/wiki/Backpropagation
Beim maschinellen Lernen ist Backpropagation ( backprop , [1] BP ) ein weit verbreiteter Algorithmus zum Trainieren von neuronalen Feedforward-Netzen .…
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Let's introduce training configure tool. This tool should find a configuration for network training with some optimal memory costs.
The Training Tool will be able to perform actions to improve the tr…
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### 📚 Documentation
It seems like there is not example anymore about how to deal with Truncated Backpropagation Through Time in the latest versions. Am I wrong?
cc @borda
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- [x] Optimise-then-discretise
- [ ] Reversible solvers
- [ ] Interpolating adjoints
- [x] Checkpointing?
- [ ] Quadrature?
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(maybe this can be documentation rather than an issue)
# How gradients of batches are calculated
In the general optimizer there is a function `optimizer_calc_batch_gradient()` that calculates the …
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I'm not satisfied by any of the explanations I have seen of backpropagation, and I want to see if I can do better.
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Hi.
[ Disclaimer: I am pretty new - to github, ANNs and NEAT as well. ]
I was wondering if executing backpropagation with a certain scheme might help training.
Is it currently possible to do so? …
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I implemented the [tiny NeRF example](https://github.com/bmild/nerf/blob/master/tiny_nerf.ipynb) using `candle` here: https://github.com/laptou/nerfy/blob/fc50dbd61c4012d1f12f556a72474b59a8b3c158/exam…
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Hi! Thanks for your great work in 3DGS!
However, as I tried your code in my custom dataset(single view datasets), it encountered an error and I can't figure out why.
```
Traceback (most recent call…
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