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It is an idea very interesting.
Think about it: from the point of view of a neuron that spikes, upon performing backpropagation, the neuron will backpropagate to its inputs for which the input sign…
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Dear Alan,
Thank you very much for publicly sharing deepwave. It is a very nice tool for testing different ideas in FWI.
I have one question regarding the Hessian calculation. You shared nice e…
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## 🐛 Bug
checkpoint_sequential breaks backpropagation when applied, making nn.Sequential models impossible to train.
## To Reproduce
Steps to reproduce the behavior:
```
torch.manual_seed…
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I think with the definition of the network and loss function, the backpropagation should be auto computed, why should we explicitly definite it in the code?
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Hello, I noticed that in your implementation of "fed_avg_dp.py", the forward propagation on the client side is done by propagating samples one by one, calculating gradients, clipping, and then adding …
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What's the version of diffusers you used?
I tried servel of them, but all failed.
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https://arxiv.org/pdf/1607.03516.pdf
In this paper, we propose a novel unsupervised domain adaptation algorithm based on deep learning for visual object recognition. Specifically, we design a new m…
leo-p updated
7 years ago
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Mocha is really nice project and has backpropagation implemented for many different layer types and neurons. However what is the best way to interface it in way to obtain one large parameter vector? I…
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## 一言でいうと
疎な重みを学習する手法の提案。密(Dense)より疎の方が、学習が早く解釈性も高くなる。疎な行列はインデックスと値で表現するのが効率が良いが、インデックスは離散値なので勾配法での学習は困難。そのためインデックスを正規分布で表現し(分散=0になると単一値に収束)連続値化することで学習する。
![image](https://user-images.githubuser…
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I believe W should be lower w to make sense. + whole Sum should be in the parenthesis.
![backprop-error](https://user-images.githubusercontent.com/108065/49720504-07349700-fcb4-11e8-9982-9c195894d0c6…