Questions tagged [lstm]

LSTM stands for Long Short-Term Memory. When we use this term most of the time we refer to a recurrent neural network or a block (part) of a bigger network.

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Shaping data for ConvLSTM for many-to-one image model

Ultimately, I am trying to obtain a binary segmentation mask for an image sequence. I have n number of image sequences, each with 500 greyscale images of size 256px by 400px. Each of these sequences ...
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209 views

How many RNN units are needed for tasks involving sequences?

I am training an RNN on the following task: Given a sequence of thirty words, predict the next word. Is there a benefit to having more than 30 cells (LSTM, GRU or plain RNN) in my network? I've seen ...
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Recurrent Neural Net (LSTM) batch size and input

I am working in Keras to build LSTM models. I understand that setting STATEFUL=FALSE means that the different batches are treated as independent when training the model. Suppose I want to build a ...
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124 views

Help framing a sequence prediction problem

I've found lots of tutorial/examples that focus on sequence prediction, which use previous time steps of the input variable(s) in order to create a forecast e.g. predict stock market price based on ...
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461 views

Stateful LSTM : Using different training window

Would it make sense for stateful LSTM (or LSTM in general) if in one epoch I feed [0-9],[10-19],[20-29],[30-39]...[990-999] (with corresponding labels/Y data) from my dataset. When I've presented all ...
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Sensor fusion using recurrent neural network: obtaining a smoothed output

I am trying to use a recurrent neural network to perform sensor fusion for an inertial measurement unit. IMUs are commonly used in conjunction with a Kalman filter (KF), which performs both fusion of ...
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135 views

LSTM querying approach

I've just realized my prediction approach for LSTM might not be correct. I am trying to predict character by character, by reading over the book. The way I've approached the problem is as follows: <...
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178 views

Using LSTM to clear up corrupted text files

LSTM can be used to generate text, can they be used to fix corrupted text files? Say that my original was: ...
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174 views

Creating an easy but not trivial dataset

I am working on the problem of automatic punctuation: given a stream of words, decide for each word whether there should be a punctuation mark after it (in future work I also want to distinguish ...
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109 views

Using LSTMs for modelling and forecasting several time series generated by the same process

My scenario is roughly the following: Imagine 500 cars, all Toyota Corollas (or whatever). While these cars have many similarities, they are not exactly identical: some of them have 1.5 liter engines ...
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953 views

Stock Price Data Manipulation for LSTM

I am trying to construct a machine learning model that predicts the difference in price from tomorrow to the day after tomorrow, using yesterday's OHLCV (open, high, low, close, volume). My models (...
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Multiple features in LSTM

It's clear how LSTM works with 1 feature. But what happens if the number of features is > 1? According to the answer proposed here, Keras creates a computational graph that executes the sequence ...
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LSTM for time series forcasting

I manipulate the time series using the different structures of the neural networks in order to make a prediction, and I wonder if there is a way to choose the parameters of the networks intelligently? ...
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35 views

Predicting sequence element based on the previous M and the following N elements

I have an array of sequences of equal length, each sequence contains 300 numbers (M=300). Each element in a sequence is a number from 1 to 9: ...
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LSTM low training/validation error but really bad predictions

I'm building a LSTM model to create an automatic drums composer. I'm following this post: LSTM Metallica I've built my model and done all the enconding, I was able to emulate the behavior of the ...
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how to build lstm with functinal api?

I am having a time series prediction problem and the data set has 4 variables. My data set is like below: ...
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33 views

Streaming sequence detection (Binary Classification) LSTM/GRU

I am currently trying to implement a model which can detect a specific sequence according to the training data which looks like the following: ...
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41 views

LSTM Multivariate, structuring data

I'll jump right to the structure of the data, and then I'll ask the question(s): For a mass X ranging from 200 to 500 units, i have 100 seconds worth of 3 output_values. So, the first few rows of the ...
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Remove subwords from BERT output

I'm trying to build a multilingual WSD system with BERT on top as the embedding layer. In order to have better performances, after BERT finishes its job (and performs Transfer Learning), I need to ...
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LONG SHORT-TERM MEMORY Hochreiter's paper BPTT

I was trying to read paper about LSTM, and I am stuck with mathematical problem. http://www.bioinf.jku.at/publications/older/2604.pdf page 4. see, |$f'_l$$_m$($net_l$$_m$)$w_l$$_m$ $_l$$_m$$_-$$_1$...
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Help understanding the Tensorboard histogram names and meaning in an LSTM Model

Can someone please help me understand what the names and shapes of the following tensorboard histogram outputs mean about an LSTM model I coded? Thank you! I understand the terms in the names like ...
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Dense? or TimeDistributedDense? after LSTM layer in Keras

Dense and TimeDistributedDense, which one is suitable after LSTM layer in Keras? For example, ...
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Masking seems not working for missing values problem in LSTM

I am trying to use LSTM to predict time series in keras. My input data shape is (1000,6,1)(samples,timesteps,features). There is some missing data in different timesteps. For example,[2,1,1]=NaN,[3,4,...
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Setting up RNN in TensorFlow for time series forecast with variable input series lengths

I am building a model with keras for time series prediction. The structure of the problem is as follows: The input is a time series of 5 numeric features The ...
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109 views

Using LSTM to forecast vehicle position - multivariate time series - Matlab

I am trying to train an LSTM model on Matlab to forecast the position of a vehicle when driving around a roundabout. My main concern right now is that my dataset consists of 4 features (X position, Y ...
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Wiggle in the initial part of an LSTM prediction

I working on using LSTMs and GRUs to make time series predictions. For the most part the predictions are pretty good. However, there seems to be a wiggle (or initial up-then-down) before the ...
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Training an LSTM with different time steps and number of features

I want to use an LSTM using Keras to make course grade predictions. My dataset includes student transcripts, which consist of courses taken and their respective grades of students. For each course, I ...
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Autoencoders for the compression of time series

I am trying to use autoencoder (simple, convolutional, LSTM) to compress time series. Here are the models I tried. Simple autoencoder: ...
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How can RNN handle variable sized inputs?

I came across this answer which is specific to Keras. But my question is at concept level. I am getting confused, How can RNN handle variable size inputs? here Let us suppose we want to do a ...
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Generate new sentences based on keywords

For example, for a domain specific neural network in Fashion, with the Keywords light, dress, orange, cotton. It could output: This gorgeous orange summer dress is great for wearing on sunny camping ...
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NLP based Data Preprocessing Method to Improve Disease Name Prediction Using CRF and Word Embedding

I built a model( using CRF along bi lstm) to Predict New Disease Name/Entities from medical text data but the problem is Disease name appears only 5,6 times in 1 text file but on average text file ...
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Simmultainiously calculting loss from target interdependend metric

Is there a way to incorporate multiple targets into one loss? Currently, I work with the Sequential() API, I guess this won't be sufficient.... I work with area predictions as targets. Each sample ...
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What is the current state-of-the-art video classification technique? [closed]

For a project I am aiming to automise the detection of goals in foosball (a.k.a. 'table football') matches. To do so I now track the ball in every frame using the openCV library in Python. To ...
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Why might an LSTM be capable of predicting an ARMA signal but not a linear combination of ARMA signals?

I have an LSTM network and am testing it on some dummy ARMA signals. I'm trying to predict the signal 5 time steps into the future. The network is capable of outperforming Naive (persistence) when ...
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hidden state of each sequence of mini-batch

I am new to Pytorch and trying to implement a lstm character level seq2seq model. What I am trying to do is: Each sequence is a list of the characters of a particular word and several words will ...
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46 views

What receives a LSTM neuron?

I'm confused about input data on LSTM neurons. I know that exist almost two form to give data to a recurrent neural network. I want to understand with a example ...
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226 views

What are the equations involved in calculation of the parameters of embedding layer?

I'm trying to perform sentiment analysis on some data using keras.I'm using embedding layer and then LSTM. I know that embedding layer decreases the sparsity of the one hot encodings of the words and ...
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192 views

How smaller does the input data get reduced in a LSTM autoencoder

Question In a LSTM autoencder, how smaller does my input data(59 features) get reduced in a latent vector, which is usually located in the middle between an encoder and a decoder? Why did the ...
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373 views

Measuring uncertainty in an LSTM network using dropout in keras/tensorflow

I've created a simple LSTM network for testing ...
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1answer
961 views

ValueError: Cannot convert a partially known TensorShape to a Tensor: (?, 256)

I'm working on a sequence to sequence approach using LSTM and a VAE with an attention mechanism. ...
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582 views

LSTM not converging

I am sorry if this questions is basic but I am quite new to NN in general. I am trying to build an LSTM to predict certain properties of a light curve (the output is 0 or 1). I build it in pytorch. ...
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153 views

How to add previous predictions for new predictions in LSTM?

I am trying to train a model on a big data sequence like this [0.2 0.1 0.1 ..... 0.4 0.8] . I create X vectors with length 60 for inputs and Y scaler numbers as ...
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584 views

How to implement Moving window with LSTM for Time Series Prediction?

I am trying to implement a moving window in my dataset. The window size=14 (for instance).After implemntinf sliding window how to prepare inputs and outputs for netwok? ...
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410 views

How to feed output of predict value back into the input using LSTM in python

The inputs here are the 3. The output here (LSTM) is the probabilities that the next x1 input ought to be. Means here I have x1x2 and x3 input values. 1st three inputs LSTM output1 and then next if x1 ...
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671 views

Keras' fit_generator() is not calling my generator

When I call Keras' fit_generator(), passing in a custom generator class I created, I see "Epoch 1/1" in the spew and that's all. It hangs right there, and the ...
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1answer
212 views

Calculation of Output in LSTM Many-to-One Architecture

I'm new to Recurrent Neural Network but I want to train my data with LSTM but I'm having a trouble to understand LSTM Many-to-One architecture. Suppose the size of my data is ...
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1answer
498 views

Metrics for presenting RNN/LSTM result

I am working on a two different architecture based on LSTM model to predict the users next action based on the previous actions. I am wondering, what is the best way to present the result? Is it okay ...
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Understanding how to use ConvLSTM for multistep ahead forecasting

I have a problem where I have transaction data for many banking accounts. The task is to train a model on historical debit/expense transactions and then forecast expense transactions for the next n ...
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Recommended model for univariate or multivariate multistep ahead time series forecasting

I have a dataset consisting of recurring and non-recurring expense transactions from bank accounts, as well as other features describing the bank account and each transation. I aggregate these ...

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