All Questions
7 questions
0votes
1answer
22views
What says the output of autoencoder?
What is the meaning of output of autuencoders? Can we say it is the noise removed version of actual dataset and should it be symmetrical?
- 21
2votes
0answers
57views
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 ...
- 21
1vote
0answers
177views
Is there any problem with the following Python+TF+Keras code for a custom loss function and network?
I am trying to code a custom loss function for variational autoencoder. I am not using mse for reconstruction loss since I am not learning p(x|z) ~ N(mu,I). Instead ...
- 1,101
0votes
1answer
2kviews
Resize instead of transposed convolutions
I'm trying to build a decoder version of ResNet, i.e. one that goes from the prelogits layer and attempts to recreate the image. I can get it working by using transposed convolutions, but the quality ...
- 101
1vote
1answer
136views
Pretraining neural net example in Aurelien Geron's book
I am testing the pretraining example in Chapter 15 of Aurélien Géron's book "Hands-On Machine Learning with Scikit-Learn and TensorFlow". The code is on his github page: here - see the example in ...
- 219
3votes
1answer
449views
How to implement a convolutional autoencoder?
I would like to implement a convolutional autoencoder in Tensorflow, but it is not clear how the decoder part should work. Each layer of the encoding, is a convolutional layer with activation ...
- 195
2votes
0answers
555views
Is there any implementation of Recursive Auto Encoders in Tensorflow?
I am looking for the implementation of Recursive Auto Encoders (RAE) in tensor flow python. I want to model English sentence representations from a sequence to sequence neural network model. RAE is ...
- 471
