Questions tagged [autoencoder]
Autoencoders are a type of neural network that learns a useful encoding for data in an unsupervised manner.
141 questions with no upvoted or accepted answers
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Unable to transform (greatly performing) Autoencoder into Variational Autoencoder
Following the procedure described in this SO question, I am trying to transform my (greatly performing) convolutional Autoencoder into a Variational version of the same Autoencoder. As explained in ...
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1answer
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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 (...
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Autoencoders for the compression of time series
I am trying to use autoencoder (simple, convolutional, LSTM) to compress time series. Here are the models I tried. Simple autoencoder: ...
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Autoencoder: Size of out_backprop doesn't match computed
This question was asked before and non of the answered worked for, I have the code ...
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Chess deep learning siamese network overfitting when shouldn't in theory
TLDR: My network is training with pairs so instead of 10^6 samples it has 10^12 samples (The number of samples squared) . With that large of a data set is shouldn't overfit but it does after very few ...
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What is the difference between KL-divergence, JS-divergence, Wasserstein distance and MMD?
I was reading about different distribution distances, and came across Kullback-Leibler divergence Jensen-Shannon divergence Wasserstein distance Maximum mean discrepancy (MMD) The book was too ...
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What is an intuitive explanation for the Importance Weighted Autoencoder?
I have been reading a paper by Burda et al. on Importance Weighted Autoencoders(IWAE) but I can't quite grasp what they mean by sampling the terms h1...hk. Do they mean you have separate models from ...
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Encoder-Decoder Sequence-to-Sequence Model for Translations in Both Directions
Is it possible to use a pre-trained sequence to sequence encoder-decoder model which translates an input text in source language to an output in target language to do an inverse translation? That is, ...
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Autoencoder behavior with All White/Black MNIST
I am using a stock auto-encoder anomaly detector from Deeplearning4j. I was getting unexpected results from my own variant of the auto-encoder, which looks for anomalies in my own (non-image) data, ...
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Using an autoencoder to mimic independent component analysis?
I'm trying to use autoencoders in keras to create a linear transformation similar to independent component analysis (ICA) (using this to denoise electroencephalographic data, time series of 64x100000 ...
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1answer
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Why VAE Encoder outputs log variance and not standard deviation?
When talking about VAE (and viewing VAE implementations), the Encoder outputs: μ, log(variance) when we train the model (the ...
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How can I use autoencoders for noise detection and removal
How can I use autoencoders for noise detection and removal in a dataset with only 2 features and no labels? How should my architecture be like, such as 2 1 1 1 2 or any other? And does the output of ...
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Convolutional autoencoder - why keras example is asymmetry model?
I'm looking on keras convolutional autoencoder example, and confused with the model structure: ...
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Deep Continious Clustering algorithm - just one output cluster
I use the DCC algorithm to cluster some data. The whole algorithm is available here, but shortly it is: construct mkNN graph of the data points (the connected components of it are the clusters). ...
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How to Save Model that has a TensorFlow Probability Regularizer?
Consider the following minimal VAE: ...
