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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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1answer
46 views

What would be the most effective self-learning algorithm for a 7 player social deduction game?

There's this 7 player social deduction game called Secret Hitler, and I have been trying to find a self-learning AI algorithm to learn how to play this game for a while. Basically, four players are ...
6
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1answer
57 views

Is there a way to understand neural networks without using the concept of brain?

Is there a way to understand, for instance, a multi-layered perceptron without hand-waving about them being similar to brains etc? For example: it is obvious that what a perceptron does is ...
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1answer
13 views

Maximize loss on non-target variable

I have a neural network that should be able to classify documents to target label A. The problem is that the network is actually classifying label B, which is an easier task. To make the problem more ...
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0answers
24 views

Understanding the partial derivative with respect to the weight matrix and bias

Say we have the layer $X W + b = Y$. I want to get $\frac{dL}{dW}$ and we assume I have $\frac{dL}{dY}$. So all I need is to find $\frac{dY}{dW}$. I know that it should be $X^T\frac{dL}{dY}$ but don'...
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1answer
38 views

Why is my neural network giving me wildly incorrect error and not changing accuracy?

My full code is as follows. I have tried to whittle it down to just the code that matters, but the problem I have is that i'm not sure what part of my network code is producing the problem. I've ...
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0answers
30 views

Training a sound localization neural network [on hold]

I am trying to train a neural network, to estimate the location (in degrees from 0 to 180) a sound is coming from. I am using tensorflow keras in python to train the model. The input data are two ...
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0answers
23 views

Did I understand deep Q leaning right? (Implementation)

Gday guys, so I tried to implement my own enviroment and agent in order to fully understand DQNs. The enviroment is a dungeon with five states. actionspace = 2 statespace = 5 !!!Action a0 is ...
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3answers
63 views

How can neural networks be used to generate rather than classify?

In my experience with Neural Nets, I have only used them to take input vectors and return binary output. But, here in a video, https://youtu.be/ajGgd9Ld-Wc?t=214, Kai Fu Lee, renowned AI Expert shows ...
3
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1answer
41 views

How do I determine the most appropriate classifier for a certain problem?

Consider a Bayesian classifier used in spam e-mail filtering. It converts an e-mail to a vector, most of the time using the bag-of-words method. Although it learns first before getting employed, it ...
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2answers
90 views

Is artificial intelligence and, in particular, neural networks being used in real-world critical applications?

Is artificial intelligence and, in particular, neural networks being used in real-world critical applications and devices? I had a discussion with my colleague who states that nobody would use ...
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1answer
71 views

An “elevator pitch” breakdown of areas of applications for Reinforcement Learning & Neural Networks vs. Genetic Algorithms

I'm looking for an "elevator pitch" breakdown of areas of applications for Reinforcement Learning & Neural Networks vs. Genetic Algorithms, both actual and theoretical. Links are welcome, but ...
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1answer
53 views

Emotional Speech Synthesis

We are a team of computer science our graduation project about EmotionalSpeech Synthesis. We've found valuable information like research papers and WaveNet, Tacotron. A website (https://www.voicery....
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0answers
20 views

Resizing effects on image recognition

I have been building a multilabel image classification model using inception v3, which uses images of size 299x299, I have been wondering what are the effects of feeding images of rectangular shapes ...
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4answers
769 views

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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2answers
40 views

How do we choose the activation function for each hidden node? [duplicate]

I am new to neural networks. I would like to use them as a fitting or forecasting method. A simple NN model that does not contain hidden layers, that is, the input nodes are directly connected to the ...
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1answer
23 views

Is this learning rate schedule increasing the learning rate?

I was reading a PyTorch code then I saw this learning rate scheduler: ...
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1answer
13 views

Independance of Gradient of feedforward neural network

Can the gradient of a feedforward neural network at a layer be assumed to be independent of the activations of the previous layers ? I read this in a paper titled "Mean Field Residual Networks: On the ...
3
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1answer
28 views

Any explanation why multiple linear layers work better than a single linear layer in practice?

It is a well-known math fact that composition of linear/affine transformations is still linear/affine. For a naive example, $\textbf{A}_1\textbf{A}_2\textbf{x}$ is simply $\textbf{A}\textbf{x}$ ...
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0answers
13 views

How to choose the suitable Neural Network Architecture for Regression Tasks

so I'm working on a Project where I want to predict the Vehicle Position from the Vehicle Data like speed, acceleration etc.. now the data that I have comes also with a timestamp for each sample ( I ...
3
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2answers
66 views

Detecting Sine Waves with a Neural Network?

I am recording the vibrations of an AC Motor (50Hz Europe) and I am trying to find out whether it is powered on or not. When I record these vibrations, I basically get the vibration values (-1 to +1) ...
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0answers
57 views

How to develop face recongiton program using CNN to obtain more than 95% accuracy? [closed]

I want to develop face recognition program using convolutional neural network. Can some one tell me steps to follow to do the same? I am new to deep learning. I want to develop it on windows using ...
2
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1answer
43 views

How can I teach a computer to play N64 games using Neural Nets?

I would like to work on a project where I teach an NN to play N64 games. To my current understanding, I would need an emulator? I can do the Machine Learning side of it, im just unsure how I can ...
3
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0answers
47 views

Are there datasets to solve differential equations in a supervised fashion?

Are there datasets to solve differential equations in a supervised fashion? More precisely, the input is a differential equation and the label should be the general solution to that differential ...
4
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2answers
64 views

What is the benefit of using identity mapping layers in deep neural networks like ResNet?

As I understand Resnet has some identity mapping layers that their task is to create the output as the same as the input of the layer. the resnet solved the problem of accuracy degrading. But what is ...
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0answers
16 views

How to train a transformer text to text model on counterexamples?

Is it possible to update the weights of a vanilla transformer model using counterexamples alongside examples? For example, from the PAWS data set, given the phrases "Although interchangeable, the ...
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0answers
15 views

Trying to separate spiral data with neural network, learning tensorflow

I am learning how to use tensorflow without keras, just to make sure I understand tensorflow directly. I created a spiral-looking datasets with 100 points of each class (200 total), and I created a ...
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0answers
15 views

How to recognize two different objects with the similar shape, but different size

I am using Mask-RCNN neural network. I retrained my network to detect and mask wheels of die-cast toy cars. I am using images, which present the side of the car (left or right). Sometimes the cars ...
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0answers
23 views

How to calculate covariance matrix of the mini-batch in the k-th layer using Python?

I am a beginner in Python. I want to calculate the covariance matrix of a mini-batch in a given hidden layer.
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2answers
264 views

What is it that humans can provide to AI that AI will need forever?

Just a thought question that came into mind from the current examples in the world. Any AI solution created so far for making the human effort lesser also has a tendency of no human effort at all. Are ...
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1answer
55 views

What order should I learn about Neural Networks?

I'm interested in learning about Neural Networks and implementing them. I'm particularly interested in GANs and LSTM networks. I understand perceptrons and basic Neural Network configuration (sigmoid ...
3
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1answer
49 views

What is the best variant of darknet to use?

pjreddie's official darknet version (link from official website here) has been forked several times. In particular I've come accross AlexeyAB's fork through this tutorial. I assume the tutorial's ...
3
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1answer
43 views

Is it possible to do K-nearest-neighbours before training DNN

The following X-shape alternated pattern can be separated quite well and super fast by K-nearest Neighbour algorithm (go to http://ml-playground.com to test it): However, DNN seems to face great ...
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0answers
58 views

What to do when an image classifier does good for a class but bad for another?

So I wrote a convolutional neural network for a binary image classification. I have around 5300 images for each class which I thought would be enough to at least give me a good accuracy on the ...
5
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0answers
21 views

What is the impact of using multiple BMUs for self-organizing maps?

Sort of a conceptual question here. I was implementing a SOM algorithm to better understand its variations and parameters and got curious about one bit: the BMU (best matching unit == the neuron that ...
4
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1answer
30 views

dimensions of hidden layer and cell state layer in LSTM

I was following some examples to get familiar with tensorflow LSTM related api, but noticed that all LSTM initialization functions require only num_units parameter which denotes number of hidden units ...
3
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0answers
23 views

Vector normalization by a neural network

I'm wondering if there is a NN that can achieve the following task: Output a unit vector that is parallel to the input vector. i.e., input a vector $\mathbf{v}\in\mathbb{R}^d$, output $\mathbf{v}/\|\...
4
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1answer
45 views

How to deal with large (or NaN) neural network's weights?

My weights go from being between 0 and 1 at initialisation to exploding into the tens of thousands in the next iteration. In the 3rd iteration they become so large that only arrays of nan values are ...
3
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1answer
34 views

GPU/TPU acceleration for neural networks with various network topologies

I was thinking about different neural network topologies for some applications. However, I am not sure how this would affect the efficiency of hardware acceleration using GPU/TPU/some other chip. If, ...
11
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1answer
189 views

What are all the different kinds of neural networks used for?

I found the following neural network cheat sheet (Cheat Sheets for AI, Neural Networks, Machine Learning, Deep Learning & Big Data). What are all these different kinds of neural networks used ...
3
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2answers
120 views

What kind of neural network architecture is suitable for variable length block-like time series data?

I'm not sure what this type of data is called, so I will give an example of the type of data I am working with: A city records its inflow and outflow of different types of vehicles every hour. More ...
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0answers
13 views

Predict the next best action based on previous lists of actions

I have the following problem. There is a software that I've written some time ago. Users enter customer's data in the system and there is a limited number of things (actions) that they can do/add - ...
2
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1answer
30 views

What sort of Neural Network is best suited to predicting a future purchase?

I have previously implemented a Neural Network with Back-Propagation that was able to learn Tic-tac-toe and could go pretty well at Connect-4. Now I'm trying to do a NN that can make a prediction. ...
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0answers
48 views

Is My Formula For a Neural Network correct?

I am creating a multi-layer neuron library in C# and doubtful of my understanding of neural network correctness as my answer even after the training of xor is always nearer 0.5. Here are the notation ...
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0answers
17 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 ...
2
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1answer
25 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. ...
3
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2answers
32 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 ...
5
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1answer
77 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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0answers
24 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 ...
4
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1answer
46 views

How does the network know which objects to track in the paper “Label-Free Supervision of Neural Networks with Physics and Domain Knowledge”?

I was reading the paper Label-Free Supervision of Neural Networks with Physics and Domain Knowledge, published at AAAI 2017, which won the best paper award. I understand the math and it makes sense. ...
3
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1answer
31 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 ...