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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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Structure and parameters of modern AI-baed chess engines

I understand some recent chess engines (like alphazero or muzero) are based on neural networks. This question is not specific to chess, any other game (e.g. go) would do, but I keep chess for ...
Manu's user avatar
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1 answer
30 views

Why do we need complex neural network designs?

If we have a sufficient number of columns (features) and a sufficient number of rows (length or volume) in a dataset that can describe a system without redundancy, we can even train a simple MLP ...
user366312's user avatar
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1 answer
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Can anyone please explain the Recurrent Neural Network calculation shown in the picture?

As you can see, this is a recurrent neural network. I want to understand how the calculations are being made. Please, be as detailed as possible no matter how simple or self-explanatory the ...
Syed_Hamza_Akbar_Ali's user avatar
0 votes
1 answer
19 views

Sparse Cross Entropy

I've been attempting to mess around with Sparse Categorical Cross Entropy Loss for the MNIST dataset. I can't seem to figure out what might be wrong with my implementation, the loss seems to ...
vxnuaj's user avatar
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Optimizing a nonlinear objective function in Deep Reinforcement Learning

I'm working on a reinforcement learning problem where the environment returns a reward pair $(r_{t+1}^{(a)}, r_{t+1}^{(b)})$. The goal is to maximize the following nonlinear objective function. $$ E[\...
Alex's user avatar
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8 votes
1 answer
2k views

When to use Tanh?

When and why would you not use Tanh? I just replaced ReLU with Tanh and my model trains about 2x faster, reaching 90% acc within 500 steps. While using ReLU it reached 90% acc in >1000 training ...
vxnuaj's user avatar
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0 votes
1 answer
42 views

xLSTM parallel computation - mismatch in dimensions

In this recent paper, a new architecture is proposed, called xLSTM. I've implemented the sequential version in PyTorch, but it's slower than I would like, so I'm now implementing the parallel version ...
Quaere Verum's user avatar
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8 views

i have a combined pandas dataframe X_train with 22200 samples and 3 features. how can i model this

more info on how data is generated: A signal is passed to a concrete specimen while increasing the frequency of the signal conductance,susceptance of concrete is measured.The experiment is performed ...
Saketh's user avatar
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0 answers
7 views

Help With Converting NumPy Function To TensorFlow Ops (graph execution issue)

I'm trying to export my command recognition model for deploymenet on embedded devices, however, I'm facing trouble when trying to encapsulate the preprocessing function into my model, that way, when I ...
Aamar_Alberm3768's user avatar
0 votes
2 answers
36 views

Neural network for specific numbers from a range (Q learning)

PROBLEM AT HAND: I have a resource (Bandwidth) of B Hz. I have to distribute the bandwidth B to users as per their requirements. For instance, voice calls would require some amount of bandwidth while ...
ANWESA ROY's user avatar
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0 answers
23 views

why isn't this network able to learn the sin function

...
Rishabh Gupta's user avatar
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0 answers
6 views

Need suggestions on neural network framework for mapping spatial polygon data to an output metric

I am working on exploring neural networks to create a model for a specific problem: I have a 3D spatial input which is defined by rectangular polygons (xmin, ymin, xmax, ymax, zcenter). For each ...
funnyfox's user avatar
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21 views

What's the overall algorithm for population evolution in the NEAT algorithm?

I am implementing NEAT from scratch using Ruby, and I'm having a hard time understanding the necessary steps and overall algorithm of what happens between generations. I have the ...
Thiago Belem's user avatar
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0 answers
15 views

NN with user as a teacher

I have similar question to the following one. Could an AI be built to learn based of interaction with a human? What category of NN is the situation when the network learns from users feedback? The NN ...
Jacek's user avatar
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0 answers
15 views

Trouble understanding why adaline works

Recently came across adaline (an improvement on perceptron) but I am having trouble understanding why adaline works. Lets take an example of 2D binary classification task. Assume line 'l' is a linear ...
Anjusha C's user avatar
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18 views

Is there any purpose of altering neural network architecture if validation loss does not decrease but training loss does?

I am training a transformer based neural network and the validation loss is not decreasing, but the training loss does decrease. I am wondering if it's possible to debug or change the architecture ...
JobHunter69's user avatar
0 votes
1 answer
34 views

Why are the tutorials and built-in datasets giving us examples that simply do not work?

I have built a classical neural network based on IMDB reviews according to the tutorial in one book about AI. 25 000 positive reviews, 25 000 negative reviews. Positive reviews result to "0",...
Jaroslav Tavgen's user avatar
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0 answers
14 views

Modeling sales of a market in a country

As a student I got a task to model a particular market in a particular country. A company, my teacher collaborate with, provided to us a sales dataset that contains: 30 product families and 60 ...
Nick's user avatar
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0 answers
24 views

How to train a simple network to predict 2D location without knowing ground truth?

There is a 2D table of known dimension width=4cm, length=6cm. We can place a disc(diameter=0.5cm) at position (x,y). If the disc stays on the table, there is a function (evaluate_position) that says ...
goldfinch's user avatar
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0 answers
32 views

Is it possible to know the family of functions a neural network approximates?

Is it possible somehow to find which family of functions a particular network approximates? For example, I have some directed graph and I use its vertices as artificial neurons (as simple McCulloch &...
Just do it's user avatar
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0 answers
29 views

Model suggestion for AI based scaling

We are exploring the idea of scaling elements within a UI container based on the given size. The container is represented by a json object, for example: ...
Sameed's user avatar
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0 answers
25 views

How to train continuous probability distributions as output from a neural network?

I'm training time series models on numerical forecasting, and I'm seeing inherent difficulty in modeling the uncertainty of the values. Time series forecasting generally has a pattern of uncertainty ...
TheEnvironmentalist's user avatar
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0 answers
16 views

1D CNN with Single vs. Two Channels for Number Image Recognition

I am taking images of numbers as input, in a convolutional neural network and building a model to predict the number. In particular, I am building a one dimensional convolutional neural network with ...
Ling Guo's user avatar
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0 answers
9 views

Can you iteratively freeze and unfreeze parts of a neural network for efficient training?

I know you can do efficient training by freezing parts of a NN, but is there any work done where part 1 of a NN is frozen and part 2 is trained, and then part 2 is frozen and part 1 is trained?
JobHunter69's user avatar
0 votes
2 answers
76 views

Which type of ML algorithm takes the least amount of time for training?

I am doing research on proteins. I have 17,000 *.CSV files on my hard disk. These files represent the chains of proteins. I want to use these ...
user366312's user avatar
11 votes
2 answers
6k views

Can you train a neural network by simply giving it ratings each time it runs?

I am currently trying to train a bot for a game I am creating. It is a 2d game with a complex map made of various shapes. The bot and character shoot bullets that are capable of ricocheting. The ...
Beluker's user avatar
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1 vote
1 answer
73 views

Is it possible that an RLNN generates actions by itself based on the info and observation state provided by the environment?

Is it possible that an RLNN generates actions by itself based on the info and observation state provided by the environment? For example a function G(s) where it takes in the state as input and ...
19216811's user avatar
0 votes
0 answers
26 views

Do neural networks have a perception of space, regardless of dimensionality?

Suppose I have a model M which outputs a three-dimensional tensor of size 3x3x3. I have another model N which outputs a one-dimensional tensor of size 27. Train both models on some arbitrary objective ...
schmixi's user avatar
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0 answers
12 views

How to knowing number of clusters when using SOM?

SOM uses neural network. The output layer of SOM should be neurons position. As the model is training, neuron's position started to moving to the closer of centroid of clusters. The output layer was ...
Muhammad Ikhwan Perwira's user avatar
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0 answers
21 views

How to Optimize model for faster Training

Below is the forward pass of my model. The input x is split about time-dimension (last-dim) which has indices till 250. Below is the code... ...
Sarvagya Porwal's user avatar
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0 answers
23 views

Influence of Unused FFN on Model Accuracy in PyTorch

I am encountering a peculiar issue with my PyTorch model where the presence of an initialized but unused FeedForward Network (FFN) affects the model's accuracy. Specifically, when the FFN is ...
Riya's user avatar
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2 votes
2 answers
438 views

Is it easier to use back-propagation or genetic algorithms to teach an artificial intelligence?

I am making a very simple neural network for a school project, and I would like to know what the best and easiest way to "teach" a neural network would be. From what I know, backpropagation ...
AlexanderB's user avatar
1 vote
0 answers
38 views

History of Neural Networks and Deep Learning

I'm interested in learning about the history of neural networks and deep learning. I've been reading about the field and am familiar with many of the developments since the 1950s. Is there a textbook,...
neuralode's user avatar
0 votes
1 answer
30 views

How do I input multi-channel Numpy array to U-net for semantic segmentation

I had lidar 3D point cloud data from semantckitti. I want to perform Semantic Segmentation on the data using U-Net. I converted the 3d point cloud data into 2D using spherical conversion and saved the ...
Leibniz 24's user avatar
0 votes
0 answers
13 views

Simplifying equation with maximum inside absolute sign

This is the formula I am working on. $|a\times \max(x,0)+b\times \max(y,0)+c \times \max(z,0)|$ Is it possible to take the maximum out of the absolute sign?
Xiaoyang Li's user avatar
0 votes
1 answer
55 views

Is it possible to simplify max(max(a,b),c)?

Like the title says, is there any way to simplify the piece wise linear function of max(max(a,b),c) into some linear combination of max(a,b), max(b,c), max(a,c)?
Xiaoyang Li's user avatar
0 votes
1 answer
22 views

Loss goes down but never below a certain treshold

I made a neural network in C#, I observe the loss goes down but never below a certain treshold. This is XOR function error graph: (The graph is every 4 samples, so for all the 4 possible combinations ...
CoffeDeveloper's user avatar
0 votes
0 answers
11 views

Adding Feature in HGNN to Count Connections to Types of Nodes

So I'm making a HGNN currently in which the number of connections a node has to other nodes of a certain type matters. Its a social network, so I care about how many person-person connections a person ...
Daniel Eban's user avatar
0 votes
1 answer
38 views

Is there a way to convert 3 layer network to 2 layer network with specific math formula?

Currently, my professor asked me to find an explicit formula to convert 3 layer network to 2 layer network. I've read some paper about the general properties of neural network, how its complexity is ...
Xiaoyang Li's user avatar
0 votes
1 answer
27 views

CNN multioutput regression architecture modification

I am working on a regression task where the model has to predict two values at the same time. The idea is that the dataset consists of 16 features, where the first 8 features represent the first value ...
lukachu03's user avatar
0 votes
0 answers
20 views

Is my C# Adam implementation correct?

I have some doubt because I incurred in different papers proposing different implementations. Also implementations on opensource projects looks different. In example there is a C++ library that ...
CoffeDeveloper's user avatar
1 vote
0 answers
37 views

Is there any standardized notation for drawing neural network diagrams?

Is there any standardized notation for drawing neural network diagrams? For example, for circuits there is a universal set of symbols used to draw different types of circuits why not for neural ...
play's user avatar
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0 votes
0 answers
8 views

Finding invariant feature areas within representation vector for each meta-class/group?

I have pairs of images which are not the same class, but are from the same meta-class/group. I have a standard CNN which produces a representation for each sample. If I have several pairs of images ...
StudentV's user avatar
0 votes
1 answer
50 views

Total loss in backpropagation

I'd say I have some understanding of backpropagation, however I am not really sure of the total loss being calculated. Let us take the example below: After 1 forward pass when I have to update the ...
xkcd101's user avatar
2 votes
1 answer
67 views

Is it possible to use Mini-Batches with Adam optimization?

Is it possible/advised to use Mini-Batch like accumulation with Adam optimization? How would that works? Do I accumulate the loss function for each sample in the batch and then run Adam, or should I ...
CoffeDeveloper's user avatar
0 votes
0 answers
23 views

Validating bundles of XMLs with inconsistent structure

The problem: We have a large number of XML bundles, and each bundle needs to meet certain criteria to be considered valid; specifically, certain values (or types of values) should belong to certain ...
SpaghettiM4ster's user avatar
0 votes
0 answers
13 views

Predicition of future batches in time series

i am working with neural networks and i want to predict the time series further ahead. I did a course on neural networks where this kind of problem is faced. But i dont really understand how it works. ...
xSequenic's user avatar
0 votes
0 answers
14 views

19 characters to one prediction

I want to read the KELM natural sentences 19 characters at a time and predict the 20th character. So i made AN enumerator that returns that moving window of characters and already encode each of the ...
CoffeDeveloper's user avatar
1 vote
0 answers
44 views

What is the best way to train a neural network with a variable number of inputs?

Suppose I have a neural network with 5 inputs: [A,B,C,D,E] There is only 1 output. The expected accuracy of the model should increase when all 5 inputs are ...
user18959's user avatar
0 votes
1 answer
67 views

How do I know that my dataset is good enough for training a neural network?

Suppose I have a clean (no outliers and normalized) dataset for training a neural network. The training process is expected to take almost a week. So, before I start training, I want to know if this ...
user366312's user avatar

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