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 |
A Python library for deep learning developed by Google. Use this tag for any on-topic question that (a) involves tensorflow either as a critical part of the question or expected answer, & (b) is not just about how to use tensorflow.
19
votes
How is Spatial Dropout in 2D implemented?
Here's a function that implements it in Tensorflow, based on tf.nn.dropout. …
4
votes
Struggling to make a neural network mimic a basic if statement
Still, if you make your weights initialisation more sensible (should be centred at zero) and standardise your inputs, then you can get this to work:
import tensorflow as tf
import numpy as np
sess = tf.InteractiveSession …
3
votes
Accepted
Why would the sampled softmax work? [word2vec]
I'm not fully across this implementation, but I think I understand what you're asking.
If we randomly skip words in the context window, we're still going to see all of them, on average.
We loop thro …
31
votes
Accepted
Loss function for autoencoders
I think the best answer to this is that the cross-entropy loss function is just not well-suited to this particular task.
In taking this approach, you are essentially saying the true MNIST data is bin …
2
votes
Image classification, narrow domain with custom labels
Plus it's fairly easy to add to an existing model, and the authors have provided a Tensorflow implementation.
It sounds like you might not have too much experience with deep learning. …