Questions tagged [neurons]
For questions about all aspects of a biological or artificial neuron.
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How many Neurons are in a single Layer Transformer?
For example, in the base model described in the original paper, each layer has the following configuration:
6 layers in the encoder
6 layers in the decoder
A model size (i.e., the dimension of the ...
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What are (all) the differences between a neuron and a perceptron?
I know two differences between a neuron and a perceptron
Neuron employs non-linear activation function and perceptron employs only a threshold activation function.
The output of a neuron is not ...
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Why some neural network models in the 1980s shown as circuit models
I am familiar with the currently popular neural network in deep learning, which has weights and is trained by gradient descent.
However, I found many papers that were popular in the 1980s and 1990s.
...
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Why is the sigmoid function interpreted as a saturating firing rate of a neuron?
I've seen several people say that sigmoids are like a saturating firing rate of a neuron but I don't see how or why they interpret it as such. I especially don't see the relationship between a "...
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Generate Image with Artificial intelligence [closed]
I am pretty new to Artificial Intelligence programming, however i do understand the basic concept.
I have an idea in my mind:
Import a JPEG Image,
Convert this Image into a 2D Array (x,y values + ...
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Do neurons of a neural network model a linear relationship?
I'm certain that this is a very naive question, but I am just beginning to look more deeply at neural networks, having only used decision tree approaches in the past. Also, my formal mathematics ...
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How do layers in an artificial neural network transform inputs to outputs?
To me, most ANN/RNN related articles don't tell me actually how the network is implemented. I know that in the ANN you'll have multiple neurons, activation function, weights, etc. But, how do you, ...
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Neural Network with varying inputs (for a game ai)
I want to create a simple game which basically consists of 2d circles shooting smaller circles at each other (to make hitbox detection easier for the start). My goal is to create an ai which adapts ...
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Can a neuron have both a bias and a threshold?
I have not seen a neuron that uses both a bias and a threshold. Why is this?
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What determines the values of weights in a neural network?
I am trying to understand how weights are actually gotten. What is generating them in a neural network? What is the algorithm that gives them certain values?
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Is input normalization built-in into mammals sensory neurons?
The spectrum of human sensory inputs seems to fall within certain ranges suggesting normalization is built-in into biological NNs?
It also adapts to circumstantial conditions, e.g. people living in a ...
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How do biological neurons weights get initialized?
When trying to map artificial neuronal models to biological facts it was not possible to find an answer regarding the biological justification of randomly initializing the weights.
Perhaps this is ...
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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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Are Modular Neural Networks more effective than large, monolithic networks at any tasks?
Modular/Multiple Neural networks (MNNs) revolve around training smaller, independent networks that can feed into each other or another higher network.
In principle, the hierarchical organization ...
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How does the degree of neuronal realism affect computing in a deep learning scenario?
Neurons can be simulated using different models that vary in the degree of biophysical realism. When designing an artificial neuronal network, I am interested in the consequences of choosing a degree ...
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Is there research that employs realistic models of neurons?
Is there research that employs realistic models of neurons? Usually, the model of a neuron for a neural network is quite simple as opposed to the realistic neuron, which involves hundreds of proteins ...
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Are AI algorithms capable of self-repair?
Do AI algorithms exist which are capable of healing themselves or regenerating a hurt area when they detect so?
For example: In humans if a certain part of brain gets hurt or removed, neighbouring ...
user9947
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How to model inhibitory synapses in the artificial neuron?
In the brain, some synapses are stimulating and some inhibiting. In the case of artificial neural networks, ReLU erases that property, since in the brain inhibition doesn't correspond to a 0 output, ...
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What makes the animal brain so special?
Whenever I read any book about neural networks or machine learning, their introductory chapter says that we haven't been able to replicate the brain's power due to its massive parallelism.
Now, in ...
user9947
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Is the neuron adequately comprehended?
It is possible that the signal handling of a neuron is outside the engineering comprehension of the most astute of human brains, even after the relationships of inputs to outputs are statistically ...
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CNNs: What happens from one neuron volume to the next?
I've gone through several descriptions of CNNs online and they all leave out a crucial part as if it were trivial.
A "volume" of neurons consists of several parallel layers ("feature ...
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Are biological neurons organized in consecutive layers as well?
I'm now reading a book titled Hands-On Machine Learning with Scikit-Learn and TensorFlow and in the Chapter 10 of the book, the author writes the following:
The architecture of biological neural ...
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Comments on my proposed "Jitter" neuron [closed]
I have an application of neural networks (standard MLP architecture) where I want to forecast a tanh output (ranging from -1 to +1) with about 1500 input features in ~700 samples.
Each sample ...
user4747
6
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How many nodes/hidden layers are required to solve a classification problem where the boundary is a sinusoidal function?
A single neuron is capable of forming a decision boundary between linearly seperable data. Is there any intuition as to how many, and in what configuration, would be necessary to correctly approximate ...
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When will the number of neurons in AI systems equal the human brain?
Based on fitting to historical data and extrapolation, when is it expected that the number of neurons in AI systems will equal those of the human brain?
I'm interested in a possible direct ...
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What is the calcium equivalent role in neural networks
I understand that neural networks model biological neurons. Each node in the network represents a neuron cell and the connections between nodes represent the connections between cells. As in nature, ...
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