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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What methods are there to detect discrimination in trained models?

I've been researching AI regulation and compliance (see my related question on law.stackexchange), and one of the big take-aways that I had is that the regulations that apply to a human will apply to ...
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75 views

Multiple sets of input in Neural network (or other form of ML)

I'm currently working on a research project where I try to apply different kinds of Machine Learning on some existing software I wrote a few years ago. This software will scan for people in the room ...
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1answer
147 views

Kohonen clustering of flowers

I have a question about output of my SOM network. I have trained my network with diffrent size, learning rate and epochs, but my output always can recognise two big clusters. Iris-setosa and Iris-...
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1answer
199 views

Unable to overfit using MLP

I'm building a 5-class classifier with a private dataset. Each data sample has 67 features and there are about 40000 samples. Samples of a particular class were duplicated to overcome class imbalance ...
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536 views

Getting worse performance when training a pre-trained model with the existing class

I am training pre-trained SSD-InceptionV2-Coco to detect the "car", which is one of the classes in mscoco label. I train the model with ~50k sample from KITTI, 500k iteration with batch size 2. I ...
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369 views

Coding CGAN paper model in Keras

I was coding a CGAN model using Keras along with the paper (https://arxiv.org/pdf/1411.1784.pdf) and I wanted to try and match the models to exactly what the paper says. I knew the models presented in ...
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21 views

Multiple centroid draw

I'm writing neural network based on neural gas algorithm (university assignment) and I remember that lecturer said that, when you generate random neuron weights at the beginning, it's worth to ...
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44 views

Shifting training data

I want to create a neural network and train it on some data, however I want to be able to create a new model without retraining it from the start. An example, I have 1000 data points in my training ...
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121 views

Classification Learning - Normalization of time series and live usage

UPDATE: The tables look messed up so i put them on pastebin for better visibility. https://pastebin.com/gDX28uVF I am using Neural Network with different learning types (for example Standard ...
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90 views

NLP proved against US legal texts

I'm new to AI development and am looking for a quality algorithm (potentially nlp?) implementation proved against US legal texts. Obviously some training would need to be done, but I've found little ...
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39 views

How to apply EOT algorithm to 3d model

Many of you have probably seen the turtle from LabSix that gets mistaken for a rifle in Google's InceptionV3 image classifier. I read the paper and I understand how they apply EOT to 2d images and on ...
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43 views

Condition Action Statement - Feed Forward Neural Network

I am trying to produce Decision Tree from Feed Forward Neural Network . The input to the feed forward neural network is Condition Action Statement for example, if airthrusthold > 90 , power up the ...
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125 views

Data prepared to linear regression. Can I use it with backpropagation?

I'm studying a Master's Degree in Artificial Intelligence and I need to learn how to use the Java Neural Network Simulator, JavaNNS, program. In one practice I have to build a neural network to use ...
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125 views

Stacked softmax layers before output

I have seen people using stacked softmax layers right at the output of neural networks designed for classification. I'm trying to understand this. Does it give any additional value? I think this could ...
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137 views

Wide & Deep Learning Explanation

I was going through "Wide & Deep Learning" tensorflow tutorial & it's quite simply explained the process. But I missed few of the things. If someone can please explain them to me, it will be ...
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47 views

Recommendations on which architecture to use to guess appointment

I'm currently developping an application which allows psychologists to manage their schedule and budget. As a proof of concept, I would like to create an intelligent appointment service. There can be ...
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170 views

Is iLQG a good algorithm for model-based planning with simple environments?

In their work Continuous Deep Q-Learning with Model-based Acceleration, the author demonstrate great results of applying Imagination Rollouts for model-based acceleration of learning. They test their ...
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44 views

Loss of precision when encoding DNN weights

This question is related to the usage of NN in critical systems (those where a failure can cause life threatening situations - autopilots for example) and the need for formal guarantees on their ...
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205 views

Can anybody explain such behavior of accuracy and loss of my Net(caffe)?

I used this project for example(framework - caffe, arhitecture of net - mod of AlexNet, 400 images are used for training). I have this result: or this: Solver: ...
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118 views

Train, Validation and Test Split for Reporting Accuracy of Neural Model and BOW

I need to report accuracies of my neural model in a conference paper as compared to various baselines. What are the accepted standards for reporting accuracies in a fair manner? Neural Model: To be ...
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70 views

seq2seq vector to letters model

I'm looking to build a sequence-to-sequence model that takes in a 2048-long vector of 1s and 0s as my input and translating it to my known output of (a variable length) 1-20 long characters (ex. ...
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1answer
102 views

How to perform back-propagation in Decoupled Neural Interfaces?

I am attempting to create a fully decoupled feed-forward neural network by using decoupled neural interfaces (DNIs) as explained in the paper Decoupled Neural Interfaces using Synthetic Gradients (...
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2answers
75 views

Difference between training accuracy and calculating accuracy with class prediction

I have trained my neural network with a dataset of 11200 images, and its validation accuracy was 96%. I saved my model and load its weights to the same neural network. I chose 738 images of my dataset ...
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1answer
135 views

How do I classify an image that contains only polygons?

I have two closed polygons, drawn as connected straight black lines on a white background. I need to classify such images in to three forms Two separate polygons One polygon encloses the other The ...
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1answer
209 views

Is it expected that during self-play reinforcement learning that player 1 or player 2 wins the majority of games?

I'm testing various learning rates and neural network configurations. I'm testing over 10000 games, with the first 2000 having random starting moves and general randomness throughout of about 20%, i.e....
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9 views

Neural network architecture with inputs and outputs being an unkown function each

I am trying to set up a neural network architecture that is able to learn the points of one function (blue curves) from the points of an other one (red curves). I think that it could be somehow ...
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How to use unmodified input in neural network?

My question may be a bit hard to explain... My neural network learns a categorical distribution, which serves as an index. This index will look up the value (= action_mean) in Input 2. From this ...
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36 views

What are the use-cases of self-replicating neural networks?

I started researching the subject of self-replication in neural networks, and unexpectedly I saw that there is not much research on this subject. I should mention I am new in the field of NNs. This ...
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38 views

Where can I find pre-trained agents able to play games with multiple stages like exploration, dialog, combat?

My goal is to create an ML model to be able to classify different game stages, e.g., dialog with a non-player character, exploration, combat with enemy, in-game menu etc. In order to do that, I am ...
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29 views

In the MINE paper, why is $\hat{G}_B$ biased, and how does the exponential moving average reduce the bias?

While reading the Mutual Information Neural Estimation (MINE) paper [1] I came across section 3.2 Correcting the bias from the stochastic gradients. The proposed method requires the computation of the ...
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11 views

Find object's location in an area using computer vision

I'm trying to see how to detect the location of a soccer ball in the field using the live camera. What are some ways to achieve this? 1- Assuming we have a fixed camera with a wide shot. How to find ...
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32 views

Dynamically adapting activation function

I am training a network through reinforcement learning. The policy network learns rotations, but depending on the actual input (state), the output of the network should be restricted to be in certain ...
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0answers
29 views

Linear output layer back propagation

So I'm stack to something that it's probably very easy but I can't get my head around it. I'm building a Neural Network that will consist of many layers with non-linear activation functions (probably ...
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1answer
37 views

Computation of initial adjoint for NODE

I'm reading the paper Neural Ordinary Differential Equations and I have a simple question about adjoint method. When we train NODE, it uses a blackbox ODESolver to compute gradients through model ...
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32 views

When do the ensemble methods beat Neural Networks?

In many applications and domains : Computer Vision, Natural Language Processsing, Image Segmentation, and many other tasks - neural networks of a certain architecture are considered to be by far the ...
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46 views

Is it better to split sequences into overlapping or non-overlapping training samples?

I have $N$ (time) sequences of data with length $2048$. Each of these sequences correseponds to a different target output. However, I know that only a small part of the sequence is needed to actually ...
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26 views

Training a CNN for semantic segmentation of large 4600x4600px images

I am trying to implement a CNN (U-Net) for semantic segmentation of similar large grayscale ~4600x4600px medical images. The area I want to segment is the empty space (gap) between a round object in ...
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1answer
57 views

Chess Neural Network - Most Optimal Input vector/matrix?

I'm wanting to build a NN that can create a policy for each possible state. I want to combine this with MCTS to eliminate randomness so when expansion occurs, I can get the probability of the move to ...
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18 views

Neural network algorithm implementation for Iris dataset

I want to use Neural network algorithm over famous Iris dataset. Iris dataset attributes names sepal length in cm sepal width in cm petal length in cm petal width in cm Sample dataset: ...
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18 views

Literature on computational modelling involving neuronal ensemblies

Straying from the current trends in deep learning, there is an, arguably, interesting idea of neuronal ensembles possibly providing an alternative to the current "layered feature detectors" ...
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19 views

Duplicating calculations in CNN-LSTM architecture

I want to use frames from video game and analyze them using CNN and LSTM. But when I have the model defined like that ...
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1answer
39 views

What are some suitable positive functions as activations of neural networks?

I am working on a deep Q-learning project. My project is different than normal deep Q-learning. The rewards of my neural network must be positive because I need their values to importance sample ...
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0answers
38 views

Is there any way where you can train a Neural Network with only one data point in the dataset?

I was working on a project involving the search for biosignatures (signs of life) on exoplanets and the probability of that planet harboring life. In this case, we know that Earth is the only planet ...
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13 views

Neural Network for locating shifting resonant frequencies

I have multiple FFT's taken from a sample at different pressures, through different analysis I can see that the resonant frequencies are shifting in the spectrum for each FFT at a different pressure. ...
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49 views

What is the efficiency of trained neural networks?

Training neural networks takes a while. My question is, how efficient is a neural network that is completely trained (assuming it's not a model that is constantly learning)? I understand that this is ...
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14 views

Why is domain adaptation and generative modelling for knowledge graphs still not applied widely in enterprise data? What are the challenges?

I see that domain adaptation and transfer learning has been widely adopted in image classification and semantic segmentation analysis. But it's still lacking in providing solutions to enterprise data, ...
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1answer
86 views

Is my “Insane Mind” design for a classifier novel or effective?

This question is in relation to a previous doubt of mine : Are there neural networks where nodes are randomly selected from among a set of nodes (in random orders and a random number of times)? I have ...
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28 views

How to understand this NN architecture?

I was reading a paper Multi-Agent Reinforcement Learning for Adaptive User Association in Dynamic mmWave Networks and I was stuck understanding the deep neural network architecture that was used. The ...
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23 views

How do non-local neural networks relate to attention and self-attention?

I've been reading non-local neural networks as explained in the original paper. My understanding is that they solve the restrained reception of local filters. I see how they are different from ...
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45 views

Why scaling reward drastically affects performance?

I have devised an gridworld-like environment where a RL agent is tasked to cover all the blank squares by passing through them. Possible actions are up, down, left, right. The reward scheme is the ...

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