Questions tagged [long-short-term-memory]

For questions related to the long-short term memory (LSTM), which refers to a recurrent neural network architecture that uses LSTM units. The first LSTM unit was proposed in 1997 by Sepp Hochreiter and Jürgen Schmidhuber in the paper "Long-Short Term Memory".

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16 views

Recurrent neural Network for survival analyses: Dealing with forecast data as feature which can exceed the number of days untill a event occurs

I am building a Recurrent Neural network (LSTM) for predicting the number of days until a Pollen season starts (when the cumulative of the year exceeds X). One of the features I am including in my ...
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21 views

Can tensorflow debugger debug a trained keras model during prediction?

I have a trained LSTM model created with keras. Is it possible to use tensorboard debugger or tensorflow debugger to debug the model during prediction runtime? Meaning that it steps through the model ...
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16 views

When stacking LSTM's, should the hidden units increase?

I'm using Weights and Biases to do some hyperparameter sweeping for a supervised sequence-to-sequence problem I'm working on. One thing I noticed is that the sweeps with a gradually increasing number ...
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19 views

Simple sequential model with LSTM which doesn't converge

I'm actually trying to create a sequential neural network in order to translate a "human" sentence in a "machine" sentence understandable by an algorithm. Like It didn't work, I've try to create a NN ...
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1answer
30 views

time-series prediction : loss going down, then stagnates with very high variance

I am trying to design a model based on LSTM cells to do time-series prediction. The ouput value is an integer in [0,13]. I have noticed that one-hot encoding it and ...
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38 views

Are there any tools I can use to debug a Keras LSTM model during prediction?

I want to be able to debug my Keras LSTM model. For example, I want to be able to check the values of the input/output gates, cell states and hidden states at every time-step during prediction. Are ...
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1answer
28 views

LSTM model on different time scales

I am a newbie to machine learning. I have an LSTM model that predicts the next output n+1 time 1, params 1, output 1 time 2, params 2, output 2 time 3, params 3, output 3 . . time n, params n, , ...
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35 views

What is the correct input shape for my LSTM network?

My professor gave us a workshop where we have to do classification of a dataset of ECG signals between healthy and unhealthy types using LSTM. Each signal consists of 1,285 time steps. What my prof ...
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49 views

How to train LSTM score prediction with very little data? (Bounty to be added)

I am trying to make a text score prediction network, and my dataset have 500 samples only. I know there is a public dataset called the ASAP Dataset. I have tested my model ...
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15 views

Make an LSTM model for each class separately

I have a dataset of some activities. The dataset contains the status of different sensors and the label of activity. T trained a model in Keras with the following architecture which models the ...
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36 views

Initial LSTM hidden state and cell

If we use LSTMCell from torch: The initial hidden and cell layers should be CONSTANT (from the first time you run the program) and saved right? Like random seeds? ...
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1answer
105 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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1answer
345 views

How to use the LSTM layer in PPO architecture?

What is the best way of using the LSTM layer in PPO architecture? Should I use them in the first layer of both actor and critic, or use them just before the final layer of these networks? Should I ...
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66 views

Why doesnt my lstm model for time series prediction improve after certain level of performance?

I created an lstm model which predicts multioutput sequeances. It takes variable length sequences as input. These sequences are padded with zero to obtain equal length. Note that the time series are ...
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63 views

Keras CRNN implementation with multiple input images

Hello I am trying to implement a CRNN with multiple input images (in my context it is 6 images) This is a regression problem and output is two real value. And for the CNN block I am thinking of using ...
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15 views

Training LSTM with class imbalance

I need to train an LSTM on some light curves, in order to find a signal (there are 2 classes signal and background). However the signal (data points corresponding to signal) is around 100 times less ...
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46 views

Why validation performance is unstable for my LSTM based model (labelling problems)?

I have trained a recurrent neural network based on 1 stack of LSTM cells. I use it to solve a classification problem. The RNN cell has 48 hidden states. The output of the last unfolded LSTM cell is ...
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41 views

Predicting sine using LSTM: Small output range and delayed output?

I have coded a very basic LSTM with forget gates (no libraries used). I'm trying to predict $0.5*sin(t + N)$ given $0.5*sin(t)$ as an exercise. I have tweaked the model, changing the output layer ...
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19 views

How to train chat bot on infinite non-stationary data?

I have continual simulated data of million sentences of two simulated persons talking to each other in a room and I want to model one of the persons speech. Now, during this period things in the room ...
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406 views

Experiment shows that LSTM does worse than Random Forest… Why?

LSTM is supposed to be the right tool to capture path-dependency in time-series data. I decided to run a simple experiment (simulation) to assess the extent to which LSTM is better able to understand ...
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26 views

Kera's (normal) LSTM uses the GPU?

I'm running Kera's LSTM (not CuDNNLSTM) but I notice my GPU is under load. I need recurrent dropout, so I can only stick with <...
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35 views

how to estimate which item is bought most using AI

Problem: Maintaining the products is a big task for a retailer. If we can estimate using AI to predict which products will sell the most, we can maintain sufficient stocks of the product without ...
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359 views

Number of nodes in hidden layer for LSTM

I am starting to learn LSTM by understanding how it is used for creating a char-RNN and had a fundamental question. Does the number of nodes in the hidden layer need to be the same as that of the ...
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42 views

How could I learn tree paths given word embeddings?

I need to map from a vector space representation onto a tree structure. A possible solution: given a word vector as input, produce a path in the tree from the root down to the node that most closely ...
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23 views

How to wire up bi-directional LSTMs?

I am interested in creating the neural network architecture described in this recent paper. However, I am not sure how to get started. Does TFLearn or Keras allow us to wire the LSTM in such ways?
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23 views

If there are several computers on a subnet, can training time be reduced by distributing the work across them?

We have multiple computers and the ability to ssh between them. What are options using either Java, C/C++, JavaScript, or Python to distribute our learning tasks? We will be using DCNN, DQN, and LSTM ...
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47 views

How to understand marginal loglikelihood objective function as loss function (explanation of an article)?

I am reading article https://allenai.org/paper-appendix/emnlp2017-wt/ http://ai2-website.s3.amazonaws.com/publications/wikitables.pdf about training neural network and the loss function is mentioned ...
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73 views

Using CNN LSTMs for prediction of images from image series

I have the following setup for a prediction task: I want to predict entire pictures from previously given pictures. In my case, only 2 pixels in every frame are neither black nor white, they are some ...
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31 views

How to visualize/interpret text prediction model results?

I am using LSTM model to predict the next xml markup from an input seed. I have trained my model on 1500 xml files. Each xml file is generated randomly. I am wondering if there is a way to visualize ...
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63 views

Learning from events. Supervised, Unsupervised or MDP?

I have a large set of simulation logs for a market simulation of which I want to learn from. The market includes: customers products (subscriptions) The customers choose products and then stick with ...
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1answer
50 views

Is there an LSTM-based unsupervised learning algorithm to label a dataset of curves?

I have a big amount of light curves (image below). I am trying to label the points as signal or background (the signal appears usually periodically, several times, for a given light curve). More ...
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17 views

Generating artificial data by means of LSTM

I got two classes namely positive and negative with 1500 samples on each a total of 3k. A sample sequence is like: ...
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1answer
19 views

What is the big fuzz about SHA-RNN versus Transformers?

In his paper introducing SHA-RNN (https://arxiv.org/pdf/1911.11423.pdf) Stephen Merity states that neglecting one direction of research (in this case LSTMs) over another (transformers) merily because ...
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20 views

Network design to learn multiple sequences of multiple categories

For learning a single sequence, LSTM only should suffice. However, my situation is different here. I have a list of sequences to learn: The sale volumes of 12 months, these are the sequences And ...
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12 views

How to feed the LSTM with different length for the latest time step?

I am having a training data set for a time-series dataset like below: ...
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16 views

Number of LSTM layers needed to learn a certain number of sequences

Theoretically, number of units for a LSTM layer is the number of hidden states or the max length of sequences as per my practice. For example, in Keras: ...
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20 views

Time series forecast for everyday for till a distant future

I have time series data for every single day from last 5 years with seasonal variation and a general increase in trend. This is what my data looks like: And I am trying to predict for every single ...
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23 views

Why doesn't my double deep Q network trained with the same training set give consistent performance?

I've written a Double DQN which can do either 1-step or multi-step learning. It also has a prioritised reply buffer. The internal network is an LSTM. My input data is a series of time series data and ...
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1answer
21 views

How do I test an LSTM-based reinforcement learning model using any Atari games in OpenAI gym?

I am writing a couple of different reinforcement learning models based on Rainbow DQN or some PG models. All of them internally use an LSTM network because my project is using time series data. I ...
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8 views

Separated LSTMs or a global one for cluster of related features

I have an $n$-dimensional time-series to apply LSTM to, $n$ is the number of features for each time point. These features can be clustered according to their concept, for example $n_1, ..., n_4$ are ...
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16 views

How to train an Encoder-Decoder LSTM for sequence to sequence prediction?

I have a dataset where for each country there is a name (string) and a multivariate time series (all integers). I am trying to use an Encoder-Decoder LSTM to forecast the next time steps in the time ...
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27 views

Why in RL function approximators with recurrent structures can learn planning?

In the paper An Investigation of Model-Free Planning the authors use ConvLSTM to learn a planning function. In particular, for each input x_t at time-step ...
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12 views

LSTM - MAPE Loss Function gives Better Results when Data is De-Scaled before Loss Calculation

I am building an LSTM for predicting a price chart. MAPE resulted in the best loss function compared to ...
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13 views

LSTM for imbalanced panel data

The available tutorials are most focused on time series prediction. I am wondering how shall we prepare the input data when it is an imbalanced data? Here is how data looks like. ...
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11 views

Is the number of bidirectional LSTMs in seq2seq model equal to the maximum length of input text/characters?

I'm confused about this aspect of RNNs while trying to learn how seq2seq encoder-decoder works at https://machinelearningmastery.com/configure-encoder-decoder-model-neural-machine-translation/. It ...
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19 views

Which NLP model to use to handle long context?

I'm trying to process product data for an e-commerce platform. The goal is to understand products' size. Just to show you some examples on how messy product dimension description is: ...
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33 views

How can I combine word2vec with tf-idf to have concatenated features?

I want to develop a focused crawler using deep reinforcement learning and a priority queue that will work as the crawler frontier. I reckon using x = (state, action)...
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31 views

Best language model to do dimension description cleansing/normalization?

I'm working on a web scraper to gather product data. product dimensions are very important to me, but they come in different formats: 32w x 45h x 23d width: 32 inch height: 45 inch depth: 12 inch .....
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14 views

Keras word ordering task

I'm trying to solve the word ordering task: given a syntactically unordered sentence, recover the right order of the words. The adopted approach is to transform each sentence in a dependency tree and ...
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24 views

My CTC loss model's loss stagnates and then outputs only blank characters

I am trying to implement BaiDu's DeepSpeech1 in keras using CTC loss, my code is below: ...