Questions tagged [autoencoders]

For questions about autoencoders, a type of unsupervised artificial network for learning efficient data codings.

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2answers
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Why are Variational autoencoder's output is blurred while GANs output is crisp and has sharp edges?

I observed in several papers that the Variational autoencoder's output is blurred while GANs output is crisp and has sharp edges. Can someone please give some intuition why that is the case? I did ...
4
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1answer
3k views

Why doesn't VAE suffer mode collapse?

Mode collapse is a common problem faced by GANs. I am curious why doesn't VAE suffer mode collapse?
2
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0answers
38 views

Autoencoder why it is special for image decoding?

I have read about auto encoder. Understood what is encoding part, and decoding part, and the latent space. Now, i tried to implement this in keras. Below is the code. ...
11
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1answer
4k views

Loss jumps abruptly when I decay the learning rate with Adam optimizer in PyTorch

I'm training an auto-encoder network with Adam optimizer (with amsgrad=True) and ...
4
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1answer
107 views

Disentangled VAE doesn't reconstruct accurate grids

I am trying to implement the disentangled VAE model according to this link. I want to understand the architecture of this model in order to customize it later. As infrastructure, I have a Linux kernel ...
4
votes
1answer
4k views

Does it make sense to use batch normalization in deep (stacked) or sparse auto-encoders?

Does it make sense to use batch normalization in deep (stacked) or sparse auto-encoders? I cannot find any resources for that. Is it safe to assume that, since it works for other DNNs, it will also ...
4
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0answers
607 views

Sparsity constraint in a deep autoencoder

Is there any way and any reason why one would introduce a sparsity constraint on a deep autoencoder? In particular, in deep autoencoders the first layer often has more units than the dimensionality ...
0
votes
1answer
54 views

What are good parameters of an encoder?

I am trying to assess an encoder in my autoencoder. I can not seem to grasp which specs make an encoder better than other one in, lets say, unsupervised learning. For example, I am trying to teach my ...
2
votes
1answer
39 views

Do Le et al. (2012) train all three autoencoder layers at a time, or just one?

Le et al. 2012 use a network of 1 billion parameters to learn neurons that respond to faces, cats, pedestrians, etc. without labels (unsupervised). Their network is built with three autoregressive ...
5
votes
1answer
482 views

How can genetic programming be used in the context of auto-encoders?

I am trying to understand how genetic programming can be used in the context of auto-encoders. Currently, I am going through 2 papers Training Feedforward Neural Networks Using Genetic Algorithms (a ...
1
vote
1answer
188 views

Equilateral and One-of-n encoding

I was reading AI For Humans Vol. 1 by Jeff Heaton when I came across the terms "equilateral encoding" and "one-of-n encoding." The explanations unfortunately made no sense to me and the reddit threads ...
6
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3answers
1k views

What is the difference between encoders and auto-encoders?

How are the layers in a encoder connected across the network for normal encoders and auto-encoders? In general, what is the difference between encoders and auto-encoders?

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