All Questions
Tagged with autoencoder unsupervised-learning
22 questions
0
votes
0
answers
119
views
pyTorch autoencoder for unsupervised classification: loss not changing
I'm new to pyTorch. I want to use the autoencoder concept to get an unsupervised classification. It seems like you should be able to use the minimum dimension from the autoencoder as input to a ...
- 1
-2
votes
1
answer
2k
views
Evaluating the performance of variational autoencoder on unlabeled data
I've designed a variational autoencoder (VAE) that clusters sequential time series data.
To evaluate the performance of VAE on labeled data, First, I run KMeans on the raw data and compare the ...
- 82
-1
votes
1
answer
95
views
Autoencoder for casualty of time series data
I am trying to figure out the link between 2-time series vectors.
for example :
X = temperature variation for one year;
Y = strain measurement for one year;
I am new to machine learning.
I cannot ...
- 1
3
votes
1
answer
3k
views
How to train a Keras model with very a big dataset?
I am trying to train an autoencoder using TensorFlow and Keras. My training data has more than 200K 512x128 unlabeled images. If I want to load the data in a matrix, its shape will be (200000, 512, ...
2
votes
1
answer
1k
views
Why flatten last encoder layer in a convolutional VAE?
I am quite new in the deep learning game, I was wondering why do we flatten the last layer of the encoder in a VAE and then give the flattened output to a linear layer, which then approximates a ...
- 35
0
votes
1
answer
162
views
Importing data to tensorflow autoencoders through ImageDataGenerator
When I try to train autoencoder by importing images as numpy arrays the training proceeds quickly with the training loss at first epoch itself < 0 and the results are also decent.
But when I import ...
- 89
0
votes
0
answers
37
views
Getting loss (binary_crossentropy) stagnated around 0.601 for this autoencoder architecture
I am working on an unsupervised image classification problem, the dataset consists of around 4700 photos of carnivores. I thought of achieving this task by constructing an autoencoder and getting the ...
2
votes
1
answer
719
views
Importance weighted autoencoder doing worse than VAE
I've been implementing VAE and IWAE models on the caltech silhouettes dataset and am having an issue where the VAE outperforms IWAE by a modest margin (test LL ~120 for VAE, ~133 for IWAE!). I don't ...
- 21
0
votes
0
answers
265
views
GPU RAM Memory fragmentation using cupy?
I am Training VAE Model on CPU it works well for 1 epoch, since I need to train it more to get good result using GPU is required, I tried training on GPU but it goes Out of Memory. Since, CPU takes 25....
user11640939
2
votes
2
answers
780
views
Anomaly Detection with Autoencoder using unlabelled Dataset (How to construct the input data)
I am new in deep learning field, i would like to ask about unlabeled dataset for Anomaly Detection using Autoencoder. my confusing part start at a few questions below:
1) some post are saying ...
0
votes
1
answer
1k
views
Unsupervised Convolutional Autoencoder is always giving blank output
I'm trying to train an autoencoder with unsupervised images. I have about 300 train images and 100 validation images. But when I inputted an unseen image to the trained autoencoder, it is giving ...
- 75
0
votes
1
answer
376
views
What is the optimal hidden units size?
Suppose we have a standard autoencoder with three layers (i.e. L1 is the input layer, L3 the output layer with #input = #output = 100 and L2 is the hidden layer (50 units)). I know the interesting ...
- 435
1
vote
0
answers
841
views
Attempt to train keras VAE on unlabeled images (input=target) using ImageDataGenerator and vae.fit_generator fails when checking model target
I am trying to adapt the keras VAE template variational_autoencoder_deconv.py found here for a non-MNIST unlabeled dataset. I am using 38,585 256x256 pixel training images and 5,000 validation images, ...
- 11
0
votes
1
answer
109
views
ValueError when training Autoencoder in Keras for unsupervised learning
I'm trying to use an autoencoder within Keras to do unsupervised classification of hyperspectral images using the Indian Pines dataset. I had started with a Project here https://github.com/...
- 1,840
1
vote
1
answer
1k
views
python tensorflow using dropout on input layer
I am using python with tf and looking for the proper way to mask some of the input while training an auto de-noising encoder for mnist data.
I tried using dropout for the input layer, same way as i am ...
- 4,859