Stack Exchange Network

Stack Exchange network consists of 175 Q&A communities including Stack Overflow, the largest, most trusted online community for developers to learn, share their knowledge, and build their careers.

Visit Stack Exchange
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
Sections title:apples
body:"apples oranges"
URL url:"*.example.com"
Favorites infavorites:mine
infavorites:1234
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
Results tagged with Search options user 87106

Artificial neural networks (ANNs) are a broad class of computational models loosely based on biological neural networks. They encompass feedforward NNs (including "deep" NNs), convolutional NNs, recurrent NNs, etc.

1
vote
0answers
Suppose I have the following architecture Where $ HA_i$ and $OA_i$ are the activated values of the hidden and output nodes respectively, and $W_i$ are the weights between nodes. I want to find …
asked Nov 10 '17 by Edv Beq
0
votes
2answers
Given a simple data set to train with neural networks where i.e.: wine quality is the categorical output and measurements of acidity, sugar, etc. are the numerical inputs. The output can be written …
asked Jan 11 by Edv Beq
2
votes
4answers
In Neural Network examples that I have seen online - sometimes the Mean Square Error is presented as $$ MSE = \frac{{1}}{2n} \sum_{i}^{n} ( \widehat{y_i} -y_i)^2 \quad (1) $$ and other times $$ …
asked Nov 10 '17 by Edv Beq
4
votes
2answers
Consider the following problem involving neural networks. The input of the neural network are $n$ paths of a diffusion model i.e.: $ dX(t)=\mu dt + \sigma dW(t) $, at some random time $t$. $$ input = …
asked Jul 9 '18 by Edv Beq
1
vote
1answer
Let $\mathbb{E}_x[g(X_t)]$ be the expected value of a random variable $X_t$ with known probability density $f_t(x)$ then for the continuous case $$\mathbb{E}[g(X_t)] = \int_{-\infty}^{\infty} g(x)f …
asked Aug 19 '18 by Edv Beq
2
votes
1answer
How many times do we sample from $Q(z|x)$ in a Variational Autoencoder? Let’s say that the autoencoder input $x$ is a single image 28x28 pixels - and $Z$ is is a one dimensional distribution. Then, t …
asked Aug 10 '18 by Edv Beq
9
votes
0answers
Online tutorials describe in depth the convolution of an image with a filter, etc; However, I have not seen one that describes the backpropagation on the filter (at least visually). First let me try …
asked Feb 2 '18 by Edv Beq
1
vote
0answers
I have simulated the relative frequency of a stochastic process by creating a very small grid say $1000$ by $1000$. The graph looks like this Now I am trying to setup a regression model by matc …
asked Aug 17 '18 by Edv Beq