Questions tagged [model-request]
Use this tag when you're looking for machine learning models that could be used to solve your specific problem.
66
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Is there some neural network that implements Least Squares?
I would like to build supervised NN that gets a matrix $A$ and vector $b$ as inputs and returns $x$ as a close result of the Least Squares algorithm for $Ax=b$.
I looked for so works in the field and ...
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21
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How to output a function given a time series data as an input using supervised learning?
I have a spreadsheet with time series data collected from two sensors, one measuring temperature and the other measuring humidity. And I also collected data from an experiment that I conducted, the ...
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18
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Is it possible to train an AI to organize frames in chronological order?
I would like to know if there is a neural network or some other kind of AI that would be able to reconstitute randomly shuffled frames into a video or slideshow that makes chronological sense? The ...
2
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1
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40
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Is there any interpretation method suitable for CNNs which do regression tasks?
I mainly tackle regression problems by CNNs, and want to find a reliable method to calculate the heatmaps for NN's results. However, I find almost all interpretation methods including CAM is used for ...
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190
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Are there Explainable GNN methods for node regression tasks?
I am wondering if there are gnn explainable methods for a regression task (e.g., traffic forecasting) where nodes have numerical features and the predicted output is a numerical value. Most of ...
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28
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What models/algorithms besides variational autoencoders can I use to transform a discrete input into a differentiable latent space?
Let's say I have a discrete input and want to transform it into a differentiable latent space. What models/algorithms besides variational autoencoders can I use?
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27
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AI model to score potential candidates, as well as output a profile of the "ideal" candidate
I'll use dating as an example for what I'm trying to accomplish.
Say I've been hired by a client to find good dating matches for them. I have a pool of potential candidates and their features (age, ...
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22
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Is there any work done on topic agnostic binary topic classification?
In the recent preprint paper Tree-based Focused Web Crawling with
Reinforcement Learning a new model is introduced to classify web pages called KwBiLSTM.
The input to this model is a featurized ...
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8
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Machine Learning Model to assess risk level of individuals of concerns (criminals) and risk level of different public saftey stations
I am working in an academic project where I want to develop ML model to assess different aspects of public safety. I want to narrow down these aspects to 2 items: 1- risk level of individuals of ...
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41
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Image classifier model which predicts objects and it's relevant areas with a combination of words
I have experience with image classification models such as CNN and Vision Transformers but this time I want to try a new thing (For me).
First please check the below image to understand what I want
...
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27
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How is it possible to detect anomalies in batches of 2 minutes of web access logs?
I have data coming from web access logs in the following form:
...
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81
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Can the output layer be connected to multiple layers?
Normaly, the output layer is only connected to the second last layer.
Is there any model that the output layer is connected to multiple layers (For example, the second last layer AND the layer before ...
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45
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Make an NN utilize other NNs as part of its decision process
Suppose I have a NN that learns to predict the time it takes a robot to move between two jobs. That's three inputs (for starters): robot, job A, job B. Not all robots travel at the same speed, and ...
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122
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How can I generalize a machine learning model to multiple curves?
I have a family of convergence curves as you can see in the image below:
I would like to train a model that fits reasonably well to all the curves at the same time in my dataset. Is it possible? Do ...
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20
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How to model a set-to-set mapping with graph neural networks?
I have a task on a heterogeneous graph where a set of nodes is given as input and some of the nodes are acceptable outputs. The dataset essentially consists of pairs (X, Y) where
X is a set of nodes ...
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Which existing model could be used for wind speed and direction prediction?
I am trying to predict the wind speed and wind direction in a graph network for a geographical area. The dataset includes the start and end nodes, the distance between them, and wind speed and ...
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117
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ML model to predict timeouts
I am new to ML and am trying to build a model to predict timeouts for a website.
The website is being monitored once a minute and the data consists of a timestamp and the response time in seconds. E.g....
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Which ML algorithm/model should I use to learn temporal dependencies between binary variables?
Let's consider the following setting:
We have 1000 binary variables (X1 ... X1000).
At each time step each of the variable can either switch (1 to 0 or 0 to 1) or stay the same.
I am looking for a ...
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78
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How might AI analyze abusive discussion using natural language grammar?
Opening thoughts
This does not only apply to SE comments, but the idea in general.
This is not a Question for Linguistics.SE; those Questions might come later, after AI analysis. Example Linguistics ...
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285
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Which approach can I use to generate forged signatures from real ones?
I am in internship period and I'm working on a signature verification problem.
This process needs real and forged signatures. All I have are the real signatures (like 30 signatures per person), and I ...
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Are there some known neural networks that, given an input image, can generate a similar image, with the same topic?
Are there some known neural networks that, given an input image, can generate a similar image, with the same topic?
Example: input = a photo of a cat on a green table, output = a generated photo of ...
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74
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Is there an approach where the output of one neural network is used to choose the next neural network?
I'd like to design a deep learning architecture in which the output of a primary neural network $M_{\theta}$ determines which neural network $N^i_{\alpha}$ in a set of secondary networks $\mathcal{N}$ ...
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141
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Is it effective to use deep learning method to produce a 1D signal as output from a 2D image as input?
I have a 1D signal that will produce a 2D image after some image processing algorithm. Would it be possible and effective to use deep learning method to reproduce the 1D signal if I have the 2D image ...
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471
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How to train an ML model to convert the given lyrics into a song by a particular singer?
I am interested in training a machine algorithm to convert the lyrics I give into a song by a particular singer.
My language is non-English (south Indian) The songs are mostly monophonic (very few ...
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84
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Non-face "deepfakes" in videos
Instead of changing faces (like James Bond to Putin) what if, given sufficient training data, I wanted to:
Remove or add some windows from a brick house?
Convert a glass of red wine to a glass of ...
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13
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What is the best way to train a text-based regressor model?
I want to build a deep learning model that can predict a continuous value (LogP in this case) given text inputs (SMILES notations in this case), the dataset is as illustrated below.
SMILES notations
...
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237
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What is the fastest multi-human pose estimation model?
I am trying to find an accurate and fast multi-person human pose estimation that I can train on with custom data. I have been searching for a little while and I may not be up-to-date on the newest ...
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37
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What type of neural network do you need if you want to detect an action or dynamic pattern instead of a static pattern?
Let's say that you want to detect if a man is running, walking, or dancing instead of just detecting a man still. What type of neural networks will you use for this purpose?
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315
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What algorithms are used in Artificial General Intelligence research?
I've read on wiki that already in 2017 there were over 40 institutions researching AGI, and I wonder what type of algorithms are being studied and developed in this field.
For example, for comparison ...
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What is the best way to train neural network with imbalanced mixed data (images and structured data)?
I have structured data and image data to solve a regression problem. One sample of structured data can be related to N images.
If I use only structured data, I get decent performance, but not enough ...
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33
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Model for direct audio-to-audio speech re-encoding
There are many resources available for text-to-audio (or vice versa) synthesis, for example Google's 'Wavenet'.
These tools do not allow the finer degree of control that may be required regarding the ...
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115
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What type of ANN architecture to choose?
I have $N$ number of teachers each of which has an input feature vector ($25$ dimensional) consisting of positive numerical values for different quality of aspects (for example: lecturing ability, ...
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165
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Which neural network can I use to solve this constrained optimisation problem?
Let $\mathcal{S}$ be the training data set, where each input $u^i \in \mathcal{S}$ has $d$ features.
I want to design an ANN so that the cost function below is minimized (the sum of the square of ...
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57
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What kind of neural network should I build to classify each instance of a time series sequence?
Let's say I have the time-series dataset below-left. I would like to train a model in such a way that, if I feed the model with an input like the test sequence below, it should be able to classify ...
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57
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What would be the state of the art image captioning deep learning model?
I saw a couple of architectures, like CNN-LSTM, with and without attention model, use of Glove vector, self-critical models, etc. I am overwhelmed looking at different notebooks and architectures, ...
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28
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Can RNNs be used to classify these time series into two classes?
My task is to classify into two classes the time series like these shown in the figure.
The figure shows one class on the left sub-figure and second one on the right. The series are shown in pairs ...
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99
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Should I use U-net to label keys in a keyboard image?
This is a 600*800 image.
Which algorithm/model should I use to get an image like the one below, in which each key is detected and labeled by a rectangle?
I guess this is some kind of a segmentation ...
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104
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Which approach should I use to classify points above and below a sine function $y(x) = A + B \sin(Cx)$?
In a linear regression problem, a line can divide a data set into two categories. So, basically, points above the line belong to category 1, and points below the ...
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Setting up a deep learning architecture for multi-dimensional data
The input data is thousands, millions of 4x1000 matrices. Each row consists of 3 small natural numbers (1000 combinations) and a corresponding real number between 0 and 1.
The output is a 1x1000 ...
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71
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Is it possible to make a neural network to solve this "reaction time test"?
I'm thinking about writing an essay on the comparison between the human nervous system (reaction time) and a neural network that does the same reaction time test. I am very new in this area, so I was ...
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1
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201
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Is there a graph neural network algorithm that can deal with a different number of input and output nodes?
I am new to graph neural networks and their applications. I have an input graph $G = \{V, E\}$ and an output graph $G' = \{V', E'\}$ where the number of nodes $V$ and $V'$ are different. I am trying ...
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Object detection approaches without anchors and NMS
The Context
From all of the problems I have worked with in computer vision, the most challenging one is the object detection. This is not because the problem itself is complex to understand or bad ...
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176
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Which neural network can approximate the function $y = x^2 + b$?
I am new to ANN. I am trying out several 'simple' algorithms to see what ANN can (or cannot) be used for and how. I played around with Conv2d once and had it recognize images successfully. Now I am ...
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78
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How many ways are there to perform image segmentation?
I'm new in Artificial Intelligence and I want to do image segmentation.
Searching I have found these ways
Digital image processing (I have read it in this book: Digital Image Processing, 4th edition)...
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3k
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Is there any existing attempt to create a deep learning model which extracts vector paths from bitmaps?
I need an algorithm to trace simple bitmaps, which only contain paths with a given stroke width.
Is there any existing attempt to create a deep learning model which extracts vector paths from bitmaps?
...
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1k
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Neural networks for sports betting
I want to design a neural network that can be used for predicting sports scores for betting, specifically for American football. What I’d like to do is create a kind of profile for each game based on ...
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232
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Is there a neural network that can output a unit vector that is parallel to the input vector?
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}/\|\...
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What are some neural network models that can use auxiliary info during training for image segmentation?
What are some deep learning models that can use supplementary information other than RGB channels for image segmentation?
For example, imagine a poorly shot image of a river (blue) that shows a gap, ...
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43
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Is any classifier not subject (or less susceptible) to fooling?
Is any classifier not subject to fooling as in here?
My question is related to this, but not an exact duplicate.
What I wanted to ask is that any classifiers inherently do not subject (or less prone) ...
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3k
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Which neural network can count the number of objects in an image?
I'm looking for a neural network architecture that excels in counting objects. For example, CNN that can output the number of balls (or any other object) in a given image.
I already found articles ...
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