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Questions tagged [bias-neuron]

68 questions
28
votes
1 answer

Should there be one bias per layer or one bias for each node?

I am looking to implement a generic neural network, with 1 input layer consisting of input nodes, 1 output layer consisting of output nodes, and N hidden layers consisting of hidden nodes. Nodes are organized into layers, with the rule that nodes…
Nate_Hirsch
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2 answers

Does bias in the convolutional layer really make a difference to the test accuracy?

I understand that bias are required in small networks, to shift the activation function. But in the case of Deep network that has multiple layers of CNN, pooling, dropout and other non -linear activations, is Bias really making a difference? The…
Aparajuli
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1 answer

Why the BIAS is necessary in ANN? Should we have separate BIAS for each layer?

I want to make a model which predicts the future response of the input signal, the architecture of my network is [3, 5, 1]: 3 inputs, 5 neurons in the hidden layer, and 1 neuron in output layer. My questions are: Should we have separate BIAS…
FaaDi AwaN
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16
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2 answers

Initial bias values for a neural network

I am currently building a CNN in tensorflow and I am initialising my weight matrix using a He normal weight initialisation. However, I am unsure how I should initialise my bias values. I am using ReLU as my activation function between each…
Nick Bishop
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14
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2 answers

Neural network bias for each neuron

I have been following Andrew NG's videos on neural networks. In these videos, he doesn't associate a bias to each and every neuron. Instead, he adds a bias unit at the head of every layer after their activations have been computed and uses this bias…
RaviTej310
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11
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3 answers

Proper way to implement biases in Neural Networks

I can make a neural network, I just need a clarification on bias implementation. Which way is better: Implement the Bias matrices B1, B2, .. Bn for each layer in their own, seperate matrix from the weight matrix, or, include the biases in the weight…
Kai
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10
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1 answer

Should an input layer include a bias neuron?

I was wondering: in a multi-layer feed-forward neural network should the input layer include a bias neuron, or this is just useful in hidden layers? If so, why?
tunnuz
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1 answer

Why is a bias neuron necessary for a backpropagating neural network that recognizes the XOR operator?

I posted a question yesterday regarding issues that I was having with my backpropagating neural network for the XOR operator. I did a little more work and realized that it may have to do with not having a bias neuron. My question is, what is the…
Vivin Paliath
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7
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1 answer

Is Bias necessarily need at Colvolution Layer?

I'm building CNN + Ensemble model for classify images with Tensorflow at Python. I crawled dog and cat images at google images. Then changed them to 126 * 126 pixel size and gray scale, add label 0 to dog, 1 to cat. CNN has 5 conv layer and 2 fc…
배준호
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7
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1 answer

Zero initialiser for biases using get_variable in tensorflow

A code I'm modifying is using tf.get_variable for weight variables, and tf.Variable for bias initialisation. After some searching, it seems that get_variable should always be favoured due to its portability in regards to sharing. So I tried to…
Keir Simmons
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1 answer

How are the bias neurons created in NEAT?

I am trying to implement simple NEAT. I read from various sources that there are 4 types of "nodes": input neurons, hidden neurons, output neurons and so-called bias neurons. I don't see which process may create bias neurons, that are depicted in…
FindingTruth
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3
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1 answer

Neural Networks sigmoid activation with bias updates

I am trying to figure out if I am creating an artificial neural network using the sigmoid activation function and using bias correctly. I want one bias node to input to all hidden nodes with static output -1 combined with its weight, and then one…
MJ Harkins
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2
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2 answers

Equation that compute a Neural Network in Matlab

I created a neural network matlab. This is the script: load dati.mat; inputs=dati(:,1:8)'; targets=dati(:,9)'; hiddenLayerSize = 10; net = patternnet(hiddenLayerSize); net.inputs{1}.processFcns =…
hancock46
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3 answers

Remove bias from the convolution if the convolution is followed by a normalization layer

def __init__(self): super().__init__() self.conv = nn.Sequential( nn.Conv2d(32, 64, kernel_size=5, stride=2), nn.BatchNorm2d(64), nn.ReLU(), nn.Conv2d(64, 64, kernel_size=3, stride=2), …
David
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When to use bias in Keras model?

I am new to modeling with Keras. I am trying to evaluate appropriate parameters for setting up the model. How do I know when you use bias vs when to turn it off?
suzieblue
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