Questions tagged [feedforward]

For questions related to the feed-forward neural network (FFNN), which is an artificial neural network wherein connections between the nodes do not form a cycle, so they are feed-forward (hence the name), as opposed to the recurrent neural network, which contains cyclic connections.

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8 views

Matrix-output for FFNN?

Turns out that it looks like I will be approximating a 100x10 matrix in my project thesis. II have the following equation $y = Dx$, where $y$ is $(100 \times 1)$, $D$ is $100 \times 10$ and $x$ is $...
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0answers
34 views

Transformer: Position-wise Feed-Forward network

The Transformer model introduced in "Attention is all you need" by Vaswani et al. incorporates a so-called position-wise feed-forward network (FFN): In addition to attention sub-layers, each of the ...
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0answers
27 views

How does a single neuron in hidden layer affect training accuracy

I'm currently a student learning about AI Networks. I've came across a statement in one of my Professor's books that a FFBP (Feed-Forward Back-Propagation) Neural Network with a single hidden layer ...
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11 views

How is the length of an input sequence related to the structure of an RNN?

My question is only with regards to the feedforward part of an RNN. I am following these steps. I am working on prediction of a time series. The time series is a toy model generated by me. It is ...
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1answer
36 views

Attempting to solve a optical character recognition task using a feed-forward network

I am doing some experimentation on neural networks, and for that I am trying to program a plain OCR task. I have learned CNNs are the best choice ,but for the time being and due to my inexperience, I ...
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0answers
46 views

Using a “is_padding” attribute in your padding instead of simply zero vectors

Typical Feed Forward Neural Networks require a fixed sized input and output. So when you have variable sized input, it seems to be common practice to pad the input with zero vectors. Why does it not ...
2
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1answer
57 views

Comparing and studying Loss Functions

I have a Deep Feedforward Neural Network $F: W \times \mathbb{R}^d \rightarrow \mathbb{R}^k$ (where $W$ is the space of the weights) with $L$ hidden layers, $m$ neurones per layer and ReLu activation. ...
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2answers
120 views

Neural network to detect “spam”?

I've inherited a neural network project at the company I work for. The person who developed gave me some very basic training to get up and running. I've maintained it for a while. The current neural ...
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1answer
252 views

Feed forward neural network using numpy for IRIS dataset

I tried to build a neural network for working on IRIS dataset using only numpy after reading an article (link: https://iamtrask.github.io/2015/07/12/basic-python-network/). I tried to search the ...
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1answer
80 views

Maximum number of neurons in a layer given number of neurons in previous layer

Consider an extremely complicated feed-forward neural network training example but with no need of computational efficiency or limiting of processing time. What is the maximum number of hidden ...
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1answer
129 views

Significance of depth of a deep neural network

How is a feed-forward neural network with few hidden layers and lots of nodes in those hidden layers different from a network with a lot of hidden layers but relatively lesser nodes in those hidden ...
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3answers
589 views

When are weights updated? (feed-forward neural network)

When am I supposed to update my weights? After each forward-, and backpropagation; and or after each completed batch? Furthermore, if I am supposed to update the weights both after each forward-, and ...
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1answer
46 views

Learning an arbitrary function using a feedforward net

I would like to get a simple example running in matlab that will use a neural net to learn an arbitrary function from input output data (basically model identification) and then be able to approximate ...
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3answers
309 views

How to create Partially Connected NNs with prespecified connections using Tensorflow?

I'd like to implement a partially connected neural network with ~3 to 4 hidden layers (a sparse deep neural network?) where I can specify which node connects to which node from the previous/next layer....
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1answer
59 views

predict waste generation

I am starting a project to predict the generation of urban waste. I have found very little information on this topic on the internet. I would be very useful advice on how to approach this topic, and ...
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1answer
52 views

Which marketing-related classification challenges is a feed forward neural network suited to solve?

I am trying to think of some marketing-related classification challenges that a feed-forward neural network would be suited for. Any ideas?
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1answer
337 views

Neural Network on EV3 Mindstorm without 3rd Party Software

I am working on a prototype for an Ev3 Neural Network. Because for competitions, we are not allowed to use Bluetooth or Wifi connections, the neural network must be made with the Ev3 block-based ...
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1answer
600 views

Compute Jacobian matrix of Deep learning model?

I am trying to implement this paper. In this paper, the author uses the forward derivative to compute the Jacobian matrix dF/dx using chain rule where F is the probability got from the last layer and ...
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2answers
128 views

Evolving network in game

So I wrote simple feed forward neural network that plays tic-tac-toe: 9 neurons in input layers: 1 - my sign, -1 - opponent's sign, 0 - empty; 9 neurons in hidden layer: value calculated using Relu; ...
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1answer
46 views

Are there any Neural network benchmarks(forward-pass speed) around?

I have a task where I would like to use a CNN. I would like to incrementally start from the fastest models, fine-tune and see whether they fit my "budget". At the moment, I'm just looking at object ...
2
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1answer
128 views

What is the difference between a feed-forward neural network and a liquid state machine?

I have used a FFNN and LSM to perform the same task, namely, to predict the sentence "How are you". The LSM gave me more accurate results than FFNN. However, the LSM did not produce perfect prediction ...
4
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1answer
100 views

What is the significance of weights in a feedforward neural network?

In a feedforward neural network the inputs are fed directly to the outputs via a series of weights. What purpose do the weights serve and how are they significant in this neural network?