Search Results
Search type | Search syntax |
---|---|
Tags | [tag] |
Exact | "words here" |
Author |
user:1234 user:me (yours) |
Score |
score:3 (3+) score:0 (none) |
Answers |
answers:3 (3+) answers:0 (none) isaccepted:yes hasaccepted:no inquestion:1234 |
Views | views:250 |
Code | code:"if (foo != bar)" |
Sections |
title:apples body:"apples oranges" |
URL | url:"*.example.com" |
Saves | in:saves |
Status |
closed:yes duplicate:no migrated:no wiki:no |
Types |
is:question is:answer |
Exclude |
-[tag] -apples |
For more details on advanced search visit our help page |
Feedforward neural networks trained to reconstruct their own input. Usually one of the hidden layers is a "bottleneck", leading to encoder->decoder interpretation.
2
votes
Autoencoder learning average of training Images
Good to see you figured out you initialized the weights to 0. But this shouldn't be a direct cause for the above effect by itself. The reason is that you have a posterior collapse, this means your dec …
9
votes
2
answers
5k
views
How does the bottleneck z dimension affect the reconstruction loss in VAEs
I have come across few VAE papers that all report a similar metric bits/dim
Many (if not all) fail to mention the bottleneck size of the z space. I do know that this would directly affect the recons …