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Questions tagged [time-series]

For questions related to time series analysis or forecasting in the context of AI and, in particular, ML.

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1answer
8 views

GPT-2 for timeseries data prediction?

Is it possible and how trivial (Or not) might it be (If possible) to retrain GPT-2 on timeseries data instead of text?
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2answers
116 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
7 views

Looking for the right type of 1D-Convolution that only considers one column/attribute

My input has the shape of n rows (time steps) and m columns (attributes). I want to train a convolutional neural network on it to predict a class. I am currently using 1D-Convolutions. I got a good ...
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0answers
30 views

Are there any ways to model markov chains from time series data?

I want to make a thing that produces a stochastic process from time series data. The time series data is recorded every hour over the year, which means 24-hour of patterns exist for 365 days. What I ...
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2answers
35 views

Conferences for Human Activity Recognition

What are some conferences for publishing papers on Deep Learning for Human Activity recognition? Do any of the major conferences have specific tracks for Human Activity Recognition?
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0answers
39 views

Spike detection in time series using Artificial Neural Networks

I'm quite new in ANNs. I intend to use ANNs for predicting spike points in time series right before they happen. I've already used LSTM for another scenario, and I know that they can be used in ...
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1answer
53 views

How to train a LSTM model with multi dimensional data

I am trying to train my model using LTSM layer in Keras (python). I have some problems regarding the data representation and feeding it into the model. My data is 184 XY coodinates encoded as a numpy ...
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0answers
37 views

What are the possible neural network architecture for linear regression or time series regression?

I started modeling a linear regression problem using dense layers (layers.dense), which works fine. I am really excited, and now I am trying to model a time series linear regression problem using CNN, ...
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0answers
34 views

Is it possible to use adversarial training to learn invariant features?

Given a set of time series data that are generated from different sites where all sites are investigating the same objective but with slightly different protocols. Is it possible to use adversarial ...
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1answer
21 views

Can HMM, MRF, or CRF be used to classify the state of a single observation, not the entire observation sequence?

I learn that the Viterbi algorithm used for Hidden Markov Model (HMM) can classify a sequence of hidden states from the corresponding observations; Markov Random Field (MRF) and Conditional Random ...
2
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1answer
68 views

LSTM Architecture

There is plenty of literature describing LSTMs in a lot of detail and how to use them for multi-variate or uni-variate forecasting problems. What I couldn't find though, is any papers or discussions ...
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1answer
30 views

Train and Test Accuracy of GRU network not increasing after 2nd epoch

So I´m currently implementing my first neural network using GRUs as a model and Keras as an implementation since it´s pretty highlevel. My problem is about the classification of 8 hour long timeseries ...
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0answers
7 views

Is there anyone who tried to discretize a continuous feature using the FDIC method(Frequency Dynamic Interval Class) ? (seems a great method)

I want to discretize a continuous attribute, I applied a lot of methods but it's clear that i'm losing information at each time, until I found the FDIC method wich seems great but I couldn't ...
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2answers
82 views

Why is it harder to achieve good results using neural network based algorithms for multi step time series forecasting?

There are different kinds of machine learning algorithms, both univariate and multivariate, that are used for time series forecasting: for example ARIMA, VAR or AR. Why is it harder (compared to ...