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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44 views

How to handle varying length of inputs that represent dependencies and recursivity in deep neural networks in case of regression?

I wanna solve a problem of regression to predict a factor. I decide to go with Deep Neural Networks as solution for my problem. The features in this problem represent loop characteristic such us loop ...
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22 views

Feature visualization on neural networks which are not for classification

Feature visualization allows to better understand neural networks by generating images that maximize the activation of a specific neuron, and therefore understand what are the abstract features that ...
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31 views

neuralnetworksanddeeplearning.com chapter 5 problems

For http://neuralnetworksanddeeplearning.com/chap5.html , could anyone suggest: 1) how to approach the derivation of expression (123) ? 2) what constitutes value ~ 0.45 ? 3) why the need of taylor ...
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59 views

Image Segmentation Prediction with cropping 256x256 grids is very slow

I have only a limited dataset (<25) with large-sized images (>1500x2000) and their pixelwise labels. The aim is to find unusual patterns in this industry dataset and highlight them. To generate ...
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20 views

Change parameter in Karaboga's code of ABC algorithm

I'm working on a problem and need to use Karaboga's code of the ABC algorithm but I have some questions... Does this formula for calculating a parameter have to be changed: ...
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64 views

Machine learning approach to facial recognition

First of all I'm very new to the field. Maybe my question is a bit too naive or even trivial... I'm currently trying to understand how can I go about recognizing different faces. Here is what I ...
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41 views

Train a recurrent neural network by concatenating time series. Is it safe?

As the title says, I want to train a Jordan network (i.e. a particular kind of recurrent neural network) using a certain number of time series. Let's say that $x_1, x_2, \ldots x_N$ are $N$ input ...
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49 views

How could I learn tree paths given word embeddings?

I need to map from a vector space representation onto a tree structure. A possible solution: given a word vector as input, produce a path in the tree from the root down to the node that most closely ...
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33 views

How Hopfield neural networks are connected with “industrial” neural networks used in machine learning?

I am trying to read https://arxiv.org/abs/1701.01727 about generalisation of Hopfield neural networks and I like the clear ideas that physics and Hamiltoanian framework can be used for modeling such ...
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32 views

Neural network backpropagation gradient descent better than conjugate gradient descent?

My understanding is that the conjugate gradient method is faster than gradient descent because it does less zig zags while descending. How come the state of the art papers I see all use gradient ...
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52 views

How to understand marginal loglikelihood objective function as loss function (explanation of an article)?

I am reading article https://allenai.org/paper-appendix/emnlp2017-wt/ http://ai2-website.s3.amazonaws.com/publications/wikitables.pdf about training neural network and the loss function is mentioned ...
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38 views

Pre priming a network for white space

When a human looks at a page. He notices the sets of letters are grouped together separated by white space. If the white space was replaced by another character say z, it would be harder to ...
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3answers
785 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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211 views

Stack for Automatic 3D Mesh Generation

Gist: Should I use LISP for a part of the following project. What are the other options. Me and a friend are planning to create a 3D Modelling Agent where a designer can :- Specify constrains on how ...
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34 views

A Binarization Method for Degraded Document Image using Artificial Neural Network and Interpolation Inpainting

I am doing a research on above cited topic but I am stuck with how to actually start the project on this. What tools are required for this kind of project? What resources are required to do project ...
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1answer
671 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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305 views

How does the target output of a Single Shot Detector (SSD) look like?

According to the paper SSD: Single Shot MultiBox Detector, for each cell in a feature map k boxes are acquired and for each box we get $c$ class scores and $4$ offsets relative to the original default ...
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81 views

Object recognition by two or more traits that are orthogonal (informally speaking)

I would really appreciate if someone could comment the following method of training neural nets providing them with some meta data (Making them more color prone only if needed, whereas now they're ...
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200 views

Training RL agent on timeseries trading data with Continous Deep Q or NAF

I am writing an MDP based agent that is supposed to learn to place bids and asks in a trading environment. The system requests 2 values (mWh energy and $, both being positive or negative). Every ...
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53 views

How to create a task-graph based neural network?

I'm trying to design a neural network with a task hierarchy. This is my idea so far: ...
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1answer
186 views

Why does the size reduce to $6 \times 6$ in the capsule networks?

I want to experiment with capsule networks on facial expression recognition (FER). For now, I am using fer2013 Kaggle dataset. One thing that I didn't understand in capsule networks was in the first ...
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41 views

Abstracting parameters of dynamic model from output time series

I am unable to identify general temrs or specific source of information for the below proposed problem. I would appreciate if the community can guide me to journal articles/books and keywords to look ...
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52 views

Feature set out of grayscale Images for training a neural network?

Previously I had trained a Neural Networkupon 20,000 character images. This Neural Net generally works well, it uses ...
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42 views

Best way to predict future frame of movie or game?

Using a neural network the method seems to be that you end up with a probability for each possible outcome. To predict the next frame in a monochrome movie of size 400x400 with 8 shades of gray, it ...
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111 views

Design neural network for generating sorting networks

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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0answers
212 views

Sigmoid output layer and Cross-Entropy cost function

I use Sigmoid activation function for neurons at output layer of my Multi-Layer Perceptron also, I use cross-entropy cost function. As I know when activation functions like Tanh is used in output ...
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153 views

Learning algorithm that filters keyboard clicking in audio feeds

When recording audio for screencasts or similar, very often the keyboard is clearly visible and can start to annoy listeners after a while. NN are quiet good at recognizing patterns. Image ...
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46 views

Training NN with 1000+ bits binary labels?

How would you design and handle training NN where the label is 1000++ bit binary (50% ones, 50% zeros). The number of labels can be small OR big in different situations. My question: is such ...
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39 views

Being able to see how tensorflow “weighs” features in classifier

Say you follow a tutorial on the tensorflow website for a wide and deep model (https://www.tensorflow.org/tutorials/wide_and_deep) I create a model based on the US census data to predict whether or ...
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0answers
38 views

Dealing with input to recurrent net with changing dimensions

I have a problem in which the dimensions of the input are increasing in row and column at each timestep. What method for preprocessing could be done or are there any architectures used for solving ...
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173 views

Trajectory classification using RNN

The problem: I want to classify a trajectory if it has some properties, for example I want to create a simple 0/1 classifier for circular trajectories. If a target is moving in a circular trajectory ...
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0answers
34 views

How to train a recurrent neural network with multiple series

I am new to neural networks. I am trying to model the run-off vs. time in a water channel after a storm event given that I know the permeability of the material in the channel, total precipitation, ...
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0answers
101 views

Modelling odd-even distinction of an integer with neural networks

Will it be possible to model the problem of odd-even distinction of an integer (not binary string representation) using neural networks?
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58 views

How do stacked denoising autoencoders work

I've been studying a recommender system which uses a collaborative deep learning approach and Bayesian learning. It has the following NN representation : I need to know the working of stacked ...
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625 views

How to teach an AI to race optimally in a racing game?

I play a racing game called Need For Madness ( some gameplay: https://www.youtube.com/watch?v=NC5uFZ-t0A8 ). NFM is a racing game, where the player can choose different cars and race and crash the ...
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169 views

Deep Learning Approaches for Color Enhancement Testing

I'm a student, and currently into image processing project and coding using OpenCV. Recently, I watched Sebastian Thrun from Udacity in TedTalks talked about AlphaGo and I'm totally interested in the ...
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35 views

Does it make sense to train an autoencoder using data from different distributions?

Say I have 500 variables and I believe those variables can be shown in a 4-dimensional latent representation which I want to learn. What I have for training is 100K samples, and those samples are ...
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106 views

When do you back-propagate errors through a neural network when using TD($\lambda$)?

I have a neural network that I'm want to use to self-play Connect Four. The neural network receives the board state and is to provide an estimate of the state's value. I would then, for each move, ...
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63 views

Orientation of data set before training simple ANN's

Well, I am new to implementing ANN's and there is something that i want to know. It maybe a bit silly though. I just wanted to know that if we have a simple data set say dependent only on a single ...
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66 views

Handling varied-size input with fixed-input network

I'm running A3C (Asynchronous Actor-Critic Agents) to learn a game where an agent needs to catch 3 rewards. The input of my network, among other things, is the relative position of the 3 rewards ...
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202 views

how to write a recurrent auto associative network?

I need to write a recurrent autoassociative network in python . I have read Explorations in Parallel Distributed Processing: A Handbook o f Models,Programs, and Exercises but I can't understand how ...
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100 views

Categorical Variable Reduction using NN

I was trying to categorical variable engineering following this paper. The code is the following: ...
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45 views

Neural Network to Interpolate Matrices

I am considering some possibilities to improve a Variable Gain nonlinear control system. One of the drawbacks of the current technique is that the change of the gains is discrete and the switching ...
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61 views

Can a CNN or MLP discover similar but untrained-on patterns?

I've been experimenting with a simple tic-tac-toe game to learn neural network programming (MLP and CNNs) with good results. I train the networks on a board positions and the best moves and the ...
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551 views

Image segmentation using SOM

I tried the below Matlab code to build SOM using selforgmap. ...
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98 views

Infer dependent variables to produce output aligned to trained data

Hypothetical example, say I wanted: P(gender,ethnicity|age,hair); so that the input would aligned to a trained dataset of: ...
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101 views

What is the relation between optimality theory and AI?

How do the basic components optimality theory apply to artificial intelligence? How is optimality theory related to neural network research?
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1answer
45 views

What is the status of the capsule networks?

What is the status of the capsule networks? I got an impression that capsule networks turned out not to be so useful in applications more complicated than the MNIST (at least according to this reddit ...
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6 views

Why won't my model train with CTC loss?

I am trying to train an LSTM using CTC loss, but the loss does not decrease when I train it. I have created a minimal example of my issue by creating training data where the network simply has to copy ...
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10 views

How to improve de-noise algorithm on low signal-to-noise ratio features?

In this plot I have features that all have a very small predictive power on y, there is a low signal-to-noise ratio. In order to de-noise them, I tried PCA and k-...