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Need a background on variational autoencoders.
Suggestions:
- Black box variational inference for state space models (http://arxiv.org/abs/1511.07367).
- Possibly a better explanation.
- Stochastic …
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# Variational Autoencoder - 지오의 논문 탐방
contents: Variational AutoEncoder의 의미 논문 설명
[https://jio0728.github.io/VAE/](https://jio0728.github.io/VAE/)
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## 一言でいうと
VAEを学習するとき、潜在表現zが無視され事前分布と事後分布を一致させる方向に学習が行われてしまうことがある(KL collapse)。これを解消するために、正規分布の代わりにVon Mises–Fisher分布(球面上の分布)を導入。KL距離からパラメーター要素(μ,σ)を除去することで、学習による一致を防いでいる
![image](https://user-im…
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None of these are necessary, I'm just listing them to keep track of all the possible small-ish changes that might improve performance or reduce the need for resources:
Normalizations:
- [ ] [Bat…
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Hi,
this is the line 190 of variational_autoencoder.py:
- 0.5 * T.sqr(tgt - mu) / T.exp(2 * ls))
where does that `2` coefficient for the log sigma come from? I did the derivations myself …
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Variational Autoencoders with Inverse Autoregressive Flows:
Allows modelling multi-modal latent distributions as could be present in contact matrix datasets.
https://bjlkeng.github.io/posts/variati…
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We could support dimensionality reduction through autoencoders. Here's a useful looking tutorial (it looks relatively straightforward to implement all of the variants in the tutorial): https://blog.k…
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This might be extension of the issues #173
I having issues with the 'variational_autoencoder_deconv.py' examples from keras github
running the script keep getting what that look like all locations …
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https://github.com/L1aoXingyu/pytorch-beginner/blob/61db1de8a2528ab50cd64b50af2268a8b3bc01a4/08-AutoEncoder/Variational_autoencoder.py#L87
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# Autoencoders and Diffusers: A Brief Comparison
A quick overview of variational and denoising autoencoders and comparing them to diffusers.
[https://eugeneyan.com/writing/autoencoders-vs-diffusers/…