Data Science Stack Exchange
Data Science Stack Exchange

Questions tagged [vae]

40 questions
19
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What is "posterior collapse" phenomenon?

I was going through this paper on Towards Text Generation with Adversarially Learned Neural Outlines and it states why the VAEs are hard to train for text generation due to this problem. The paper states the model ends up relying solely on the…
thanatoz
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Train a GAN on "before and after" images of dental surgeries

I want a GAN to train on "before and after" images of dental surgeries; so that it can generate "after" pictures for fresh patients. Input images are like these:…
Lakshay Dulani
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Why maximize ELBO in the variational autoencoder?

For a variational autoencoder, we have that: $$\mathcal{L}(x,\theta,\phi) := \mathbb{E}_{z \sim q_\phi(z|x)}[\log p_{\theta}(x|z)] -KL[q_{\phi}(z|x) ||p(z)] $$ This is called the variational lower bound or evidence lower bound (ELBO). But I think…
A_P
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ValueError: Cannot convert a partially known TensorShape to a Tensor: (?, 256)

I'm working on a sequence to sequence approach using LSTM and a VAE with an attention mechanism. p = np.random.permutation(len(input_data)) input_data = input_data[p] teacher_data = teacher_data[p] target_data = target_data[p] BUFFER_SIZE =…
Kahina
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1D CNN Variational Autoencoder Conv1D Size

I am trying to create a 1D variational autoencoder to take in a 931x1 vector as input, but I have been having trouble with two things: Getting the output size of 931, since maxpooling and upsampling gives even sizes Getting the layer sizes…
Celi Manu
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4
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Why KL Divergence instead of Cross-entropy in VAE

I understand how KL divergence provides us with a measure of how one probability distribution is different from a second, reference probability distribution. But why are they particularly used (instead of cross-entropy) in VAE (which is…
Bahauddin Omar
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VAE generates bad images. due to unbalanced loss functions?

I'm training a variational autoencoder on CelebA dataset using TensorFlow.keras The problem I'm facing is that the generated images are not diverse enough and look kinda bad. (new) Example: What I think: it's bad because the reconstruction and KL…
Lidor shimoni
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Intractability in Variational Autoencoders

I'm having difficulty understanding when integrals are intractable in variational inference problems. In a variational autoencoder with observation $x$ and latent variable $z$ we want to maximize data likelihood $p_\theta (x) = \prod_{i=1}^N…
KRL
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3
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What do we visualize in showing a VAE latent space?

I am trying to wrap my head around VAE's and have trouble understanding what is being visualized when people make scatter plots of the latent space. I think I understand the bottleneck concept; we go from $N$ input dimensions to $H$ hidden…
ITA
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How does variational autoencoders actually work in comparison to GAN?

I want to know about how variational autoencoders work. I am currently working in a company and we want to incorporate variational autoencoders for creating synthetic data. I have questions regarding this method though, is this the only way to…
NevMthw
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What are the Most Dissimilar MNIST Digits?

Using whatever definition of dissimilarity over sets that you'd like, what are the most dissimilar two digits in MNIST? I was thinking that a reasonable approach to answering the question would be to pass the two sets through some state-of-the-art…
JoeTheShmoe
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Can VAEs be used to generate multivariate data?

Most of the tutorials online seem to use VAEs to generate images and use CNNs to generate data. I am working on a game with multivariate data consisting of character position and the character attributes to train a VAE. I was wondering if it was…
Alex
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Latent variable graph in Variational Autoencoder

I followed this Keras documentation guide about Auto Encoders. At the end of the documentation there is the graph of the latent variable z: But I can not understand and how to interpret the plot, and how should the plot change as the…
Turned Capacitor
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Training with different datasets for the same better VAE model yields poor results

The VAE model I used here https://github.com/keras-team/keras-io/blob/master/examples/generative/vae.py. It can produce very well results for the minist and fashion minist dataset. But when I use my datasets, the results are pretty terrible. So I…
Guo Ray
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pytorch code for VAE for MINST forces mu and logvar to zero

I am new to pytorch and trying to implement a VAE for MNIST data. When I try to train my model, it appears that the model forces mu and logvar to zero (or something very close to zero) independent of the input. In a way it appears that it is failing…
yorkiva
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