Questions tagged [vae]

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3
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1answer
91 views

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:****...
0
votes
1answer
40 views

How to make custom callback in keras to generate sample image in VAE training?

I'm training a simple VAE model on 64*64 images and I would like to see the images generated after every epoch or every couple batches to see the progress. when I train the model I wait until the ...
0
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0answers
3 views

What is achieved by converting the latent space to normal distribution in VAE?

Instead of forwarding the latent values to the decoder directly, VAEs use them to calculate a mean and a standard deviation. The input to the decoder is then sampled from the corresponding normal ...
8
votes
1answer
355 views

Train a GAN on “before and after” images of dental surgeries [closed]

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: https://img.webmd.com/dtmcms/live/...
1
vote
2answers
32 views

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 ...
0
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0answers
147 views

InvalidArgumentError: Incompatible shapes while training

InvalidArgumentError: Incompatible shapes: [15,31744] vs. [15,31680][[{{node loss_4/output_loss/logistic_loss/mul}}]] Has anyone of you ever got this kind of ...
1
vote
0answers
68 views

Variational Autoencoder: Negative log likelihood not optimized

I am using the auto encoding variational Bayes algorithm for one unsupervised object detection task. In the loss function, the reconstruction loss is calculated as the log likelihood of the original ...
1
vote
0answers
33 views

How to estimate total correlation KL[q(z)||Πjq(zj)] of VAE after training (useful for latents disentanglement evaluation)

FactorVAE and β-TCVAE both use total correlation (TC) batch estimation for their objectives. Where TC is: $$ KL\bigl( q(z)||\prod\nolimits_{j} q(z_{j})\bigr) $$ both estimates are applied to $q(z|x)$...
0
votes
2answers
58 views

What is the meaning of “probability distribution of p(x)” of something uncountable?

I'm studying VAE and new to both of the neural network and the statistic. After some researches, I could understand the rough concept of VAE. But what makes me confused is, the meaning of probability ...
0
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0answers
8 views

Post Training Sampling from a unit Gaussian?

During the training of a VAE, we sample Z from N(mu, sigma) ( = Q(Z|X) ) and then feed it to the decoder for reconstruction. Why do we, then, feed Z ~ N(0,1) to the decoder after the training is ...
2
votes
1answer
235 views

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 ...
4
votes
1answer
827 views

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 ...
2
votes
1answer
910 views

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. ...
2
votes
1answer
1k views

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 ...
0
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0answers
920 views

InvalidArgumentError: incompatible shapes: [32,153] vs [32,5] , when using VAE

I'm working on a sequence to sequence model using LSTM, the model worked perfectly with an autoencoder, but when I try to use a Variational autoencoder by adding the mean and deviation layer and ...
5
votes
1answer
4k views

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 ...