Questions tagged [neural-networks]

For questions about a artificial networks, such as MLPs, CNNs, RNNs, LSTM, and GRU networks, their variants or any other AI system components that qualify as a neural networks in that they are, in part, inspired by biological neural networks.

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7 views

Why does my NN produce Nan values after something like the 3rd iteration?

After about the 2nd or 3rd iteration/epoch, the outputs from my forward prop all contain NaN values. The softmax function produces extreme values which probably is the reason for this. However, I am ...
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14 views

Employing an Agent to Learn through Undirected Exploration?

So, I’m looking to automate some tasks at my job. I work at an engineering company. One of my tasks is produce these “reports” in excel that track some design metrics in our company. It’s a soul ...
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1answer
22 views

Neural network does not give out the required out put?

Made a neural network using tensor flows that was supposed matches an Ip to one of the 7 type of vulnerabilities and gives out what type of vulnerability that IP has. ...
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2answers
19 views

How can we find find the input image which maximizes the class-probability for an ANN?

Let's assume we have an ANN which takes a vector $x\in R^D$, representing an image, and classifies it over two classes. The output is a vector of probabilities $N(x)=(p(x\in C_1), p(x\in C_2))^T$ and ...
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1answer
42 views

Why evolutionary training of neural networks is not popular?

Evolutionary algorithms are mentioned in some sources as possible to be used to train a neural network (finding weights, not hyperparameters), however I have not heard about one practical application ...
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22 views

How to get same accuracy with identical models in Keras and Tensorflow?

As we all know Keras backend uses Tensorflow and so it should give out same kind of results when we provide same parameters, hyper-parameters, weights and biases initialisation at each layer, but ...
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1answer
23 views

Query on another perspective on Deep Learning

At least at some level, maybe not end-to-end always, but Deep Learning always learns a function, essentially a mapping from a Domain to a Range. The Domain and Range, at least in most cases, would be ...
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28 views

Get the position of an object, out of an image

I have some images with a fixed background and a single object on them which is placed, in each image, at a different position on that background. I want to find a way to extract, in an unsupervised ...
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13 views

A2C for the game of Hanabi underfits

I am trying to solve the game of Hanabi (paper describing game) with actor-critic algorithm. I took code for the environment from the Deepmind's repository and implemented a2c algorithm myself. From ...
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26 views

Neural Network training on one example to try overfitting leads to strange predictions

tldr; if I train the network on 1 training example, the outcome sometimes makes no sense at all, sometimes is as expected. If I train it on more examples and higher iterations, the network, which ...
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1answer
31 views

How do policy gradients compute an infinite probability distribution from a neural network

Do neural networks compute the probability distribution for policy gradient methods. If so, how do they compute an infinite probability distribution? How do you represent a continuous action policy ...
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1answer
22 views

Image classification with an associated matrix

I have a dataset of images with 9 different classes. However, there are different categories with the same type of associated image and only can be differentiated with an associated matrix in my ...
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16 views

Handwritten digits recognition during the process of writing

I know how to train a NN for recognizing handwritten digits (e.g. using the MNIST database). I'm wondering how to accomplish the same "online", which is during the process of writing e.g. I'm writing ...
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2answers
35 views

How to express accuracy of a regression ANN that uses MSE loss function?

I have a regression MLP network with all input values between 0 and 1, and am using MSE for the loss function. The minimum MSE over the validation sample set comes to 0.019. So how to express the '...
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11 views

CBIR Evaluation on contextually different data

How good would a CBIR system trained on a dataset, for example, DELF, trained on the Google Landmarks dataset, perform when evaluated on a contextually different dataset such as the WANG or the COREL ...
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1answer
76 views

Why isn't my Neural Network based calculator working?

I am playing around with neural networks in Tensorflow and I figured an interesting test would be whether I can write a calculator using a Tensorflow Neural Network. I started with simple addition ...
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1answer
56 views

How can the derivative of a neural network be calculated, given no mathematical expression?

Neural networks (NNs) are used as approximators in reinforcement learning (RL). To update the policy in RL, the actor network's gradients w.r.t its weights are needed. Since NN doesn't have a ...
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27 views

why the sigmoid function will be 1 and 0 if we use a fully connected layer that produce a big enough positive(res negative )output

HI I am using a fully connected network that uses sigmoid if we feed a a big enough weights the sigmoid function will finally become 1 or 0 , is there any solution to avoid this ? and will this lead ...
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37 views

Can neural networks output the rules it is using?

I have made a neural network using TensorFlow that is able to identify IP addresses that are likely to have a vulnerability of type A. I want to output the rule it has made for this identification.
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21 views

Extract personal information about a person

I need to extract personal information about a person from a list of documents and summarize it to the user. If there are 2 people with the same name, the correct person should be identified. If the ...
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1answer
35 views

How many hidden layers are needed for this training data set

I'm trying to separate classes in 3D space, the data are as in the sketch below: There are 3 classes: 0,1,2; and with the look into the sketch, it seems that I need 3 planes to separate the classes, ...
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10 views

Is there any reason to believe a ml pipeline that works on dataset A will work on dataset B where both have similar meta features?

I’m working on generating an automl pipeline(a combination of data cleaning and transformation algorithms applied to a dataset then generate a model) that works on a new dataset by looking for past ...
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0answers
19 views

Can two neural networks be better instead of one with a categorical feature?

Let's assume, that I have a neural network with few numerical features and one binary categorical feature. The network in this case is used for regression. I wonder if such a neural network can ...
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1answer
36 views

Generate credit cards dataset for locating number region

Currently I'm working on a project for scanning credit card and text extraction from cards. So first of all I decided to preprocess my images with some filters like thresholding, dilation and some ...
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36 views

Which approaches are best suited for text deblurring?

I want to deblur text images using deep learning. Which approaches are best suited for the task? Any example networks? Is unsupervised network the best approach? GAN or cycle GAN for these purposes? ...
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20 views

PPO: action std or entropy for exploration?

When trying to implement my own PPO (Proximal Policy Optimizer), I came accross two different implementations : Exploration with action std : Collect trajectories on ...
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1answer
22 views

Structure discrepancy of an LSTM?

I've found multiple depictions of how an LSTM cell operates. See 2 below: and Each of these images suggest the hidden state is utilised differently. On the top diagram, it is shown that the hidden ...
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21 views

Reference request: one-hot encoding outperforming random orthogonal encoding

I experimented with a CNN operating on texts encoded as sequences of character vectors, where characters are encoded as one-hot vectors in one embedding and as random unit length pairwise orthogonal ...
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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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40 views

Is there data available about successful neural network architectures?

I am curious to if there is data available for MLP architectures in use today, their initial architecture, the steps that were taken to improve the architecture to an acceptable state and what the ...
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0answers
15 views

Applying ML algorithms to data-sets with similar meta-features?

Is there any grounds for assuming an algorithms applied to a data-set that created a decently accurate model will perform as well on a different data-set with meta-features chosen and evaluated by ...
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1answer
43 views

Should the biases be zero or randomly initialised?

I'm initialising DNN of shape [2 inputs, 2 hiddens, 1 output] with these weights and biases: ...
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2answers
70 views

What are some examples of LSTM architectures?

I've been doing some class assignments recently on building various neural networks. For convolutional networks, there are several well-known architectures such as LeNet, VGG etc. Such "classic" ...
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14 views

Confusion on how skip gram implementation is formulated

I'm using this source to understand the skip gram model. Let's say the context size is $4$ ($2$ context words on each side of the target word). This image illustrates how training examples are ...
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23 views

How to update Loss Function parameter after compilation

I used following custom loss function. ...
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0answers
12 views

AlphaZero value at root node not being affected by training

I have written my own AlphaZero implementation and started training it recently. Problem is, I am 99% sure there is a mistake and I do not know how to tackle this, since I cannot explain it. I am new ...
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2answers
108 views

Help me to understand AI neural networks basics please [closed]

I have read some about AI and I know these bubble graphs and how they supposed to work, the different training concepts ect. But I totally fail to understand, how to put it in code. Most ...
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0answers
36 views

Feasibility of using machine learning to obtain self-consistent solutions

I am a physicist and I don't have much background on machine learning or deep learning except taking a couple of courses on statistics. In physics, we often simulate a model by means of two-way ...
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1answer
40 views

Have neural networks something to offer which goes beyond regression analysis?

Neural networks are perceived as a powerful regression tool. If a dataset contains of input/output relations, the neural network can adjust it's internal parameters to interpolate the missing data. In ...
2
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1answer
38 views

Understanding the intuition behind Content Loss (Neural Style Transfer)

I'm trying to understand the intuition behind how the Content Loss is calculated in a Neural Style Transfer. I'm reading from an articles: https://medium.com/mlreview/making-ai-art-with-style-transfer-...
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1answer
33 views

What are the differences between Bytenet and Wavenet?

I recently read Bytenet and Wavenet and I was curious why the first model is not as popular as the second. From my understanding, Bytenet can be seen as a seq2seq model where the encoder and the ...
2
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1answer
43 views

Video engagement analysis with deep learning

I am trying to rank video scenes/frames based on how appealing they are for a viewer. Basically, how "interesting" or "attractive" a scene inside a video can be for a viewer. My final goal is to ...
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1answer
114 views

Can a neural net learn to read?

I am a student of last year of computer engineering and lately I have been very interested in AI. Fields such as ML and DL seem very disruptive to me. A few months ago I saw an interview of Bill ...
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1answer
48 views

Why do I get a straight line as an output from a neural network?

I am using feedforward neural network for regression and what I get as a result of prediction is a constant value visible on the graph below: Data I use are typical standardised tabular numbers. The ...
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1answer
25 views

Combining mean pooling and max pooling

Is it popular or effective to concatenate the results of mean-pooling and max-pooling? To get the invariance of the latter and the expressivity of the former.
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0answers
24 views

Initial LSTM hidden state and cell

If we use LSTMCell from torch: The initial hidden and cell layers should be CONSTANT (from the first time you run the program) and saved right? Like random seeds? ...
2
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1answer
43 views

Is normalizing the data a way to improve generalization?

There are many known ways to overcome overfitting or make a model generalize better to unseen data. Here I would like to ask if normalizing/standardizing/similiraizing the train and test data is a ...
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0answers
30 views

Is it possible to control asymptotic behaviour of neural network models?

Is it possible to specify what the asymptotic behaviour of a Neural Networks (NN) model should be? I am thinking on NN which try to learn a mapping $\vec y=f(\vec x)$ with $\vec x$ a vector of ...
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0answers
40 views

CNN - Visualizing images near decision boundary - Pixels inexplicably tend to edges

We are exploring the images classified by a CNN at its decision boundary, using Genetic Algorithms to generate them. We have created a fine-tuned binary grayscale image classifier for cats. As the ...
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15 views

Suggestions for Deep Learning for regression on huge 3D volumes

I have a dataset of 3D images (volumes) with dimensions 400x250x400. For each input image I have an output of the same dimensions. I would like to train a machine learning (or deep learning) model on ...