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Questions tagged [network-design]

For questions about the design of neural networks. So, for example, when you don't know how many layers or which type of layer you need to use, you can use this tag.

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How to output an integer/discrete number n with a single output neuron?

Say I have a game with 4 base actions [left, right, up, down] and then a value n, which determines how many times the chosen action is repeated. For example, action = left, n = 3 -> go left 3 times....
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How can Siamese Neural Networks accept a variable number of inputs?

Traditionally, Siamese Neural Networks have two inputs. With some tweaking, you can get them to accept any number of inputs. What I don't understand is how to get them to accept variable numbers of ...
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Network design to learn multiple sequences of multiple categories

For learning a single sequence, LSTM only should suffice. However, my situation is different here. I have a list of sequences to learn: The sale volumes of 12 months, these are the sequences And ...
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Number of LSTM layers needed to learn a certain number of sequences

Theoretically, number of units for a LSTM layer is the number of hidden states or the max length of sequences as per my practice. For example, in Keras: ...
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4 votes
2 answers
82 views

What kind of output should be used for predicting angles in DNNs?

I am building a model which predicts angles as output. What are the different kinds of outputs that can be used to predict angles? For example, output the angle in radians cyclic nature of the ...
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  • 179
2 votes
2 answers
572 views

Which neural network should I use to approximate a specific but unknown function?

We have convolutional neural networks and recurrent neural networks for analyzing, respectively, images and sequential data. Now, suppose I want to approximate the unknown function $f(x,y) = \sin(2\pi ...
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  • 31
4 votes
1 answer
2k views

How to constraint the output value of a neural network?

I am training a deep neural network. There is a constraint on the output value of the neural network (e.g. the output has to be between 0 and 180). I think some possible solutions are using sigmoid, ...
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  • 41
1 vote
1 answer
843 views

How would I go about creating a neural network that outputs a non-binary number?

I would like to create a neural network, which, given the training data (e.g. 58, 2) outputs a non-binary number (e.g 100). Perhaps I am not searching for the correct thing, but all the examples I ...
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1 vote
0 answers
121 views

How would you design a neural network that generates the positions of comparators in a sorting network given a set of numbers?

How would you design a neural network that generates the positions of comparators in a sorting network given a set of numbers? I've tried to modify some already implemented networks that given a set ...
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  • 119
2 votes
1 answer
522 views

How to design a neural network to predict the quadrant where a given point lies?

I've written a single perceptron that can predict whether a point is above or below a straight-line graph, given the correct training data and using a sign activation function. Now, I'm trying to ...
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22 votes
4 answers
8k views

How could we build a neural network that is invariant to permutations of the inputs?

Given a neural network $f$ that takes as input $n$ data points: $x_1, \dots, x_n$. We say $f$ is permutation invariant if $$f(x_1 ... x_n) = f(\sigma(x_1 ... x_n))$$ for any permutation $\sigma$. How ...
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8 votes
2 answers
307 views

How to design a neural network when the number of inputs is variable?

I'm looking to design a neural network that can predict which runner wins in a sports game, where the number of runners varies between 2-10. In each case, specific data about the individual runners (...
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  • 191
5 votes
1 answer
313 views

How do I design a neural network that breaks a 5-letter word into its corresponding syllables?

I am going to design a neural network which will be able to break a 5-letter word into its corresponding syllables (hybrid syllables, I mean it will not strictly adhere to grammatical syllable rules ...
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