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Hi ! Thanks for your great efforts. It helped me a lot to understand very basic concepts.
It would be great if you could add more explanation to the back-propagation and training a simple neural net…
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Run and test the libraries for neat, and think about adding backpropagation to it
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### Is there an existing issue for this?
- [X] I have searched the existing issues
### Feature Description
This feature will implement the core algorithm for training neural networks without using …
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Just wondering if you had any plans to implement cross_entropy_loss or backpropagation for training.
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I want to use `mkpts_0, mkpts_1 = xfeat.match_xfeat(im1, im2, top_k = 4096)` to **optimize** different targets based on the distance between matches.
However, even if I remove the inference stuff, th…
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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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## Description and motivation
I'm trying to make inference with different timesteps on a neural network that's trained with Feedback Alignment from biotorch, however it is showing the same accuracy…
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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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```def update_weights(inputs, outputs, weights, lr):
original_weights = deepcopy(weights)
temp_weights = deepcopy(weights)
updated_weights = deepcopy(weights)
original_loss = feed…
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Support for multi-layer perceptrons via backpropagation.