Questions tagged [recurrent-neural-network]

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What are practical uses of MP Neurons?

Are there any practical uses of MP neurons in any industry/application or any situation where MP neuron outperforms in some metric other methods? Or is it only just used in teaching as a basis to ...
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What are the evaluation metrics we can use for RNN models?

I'm working on a few RNN (Recurrent Neural Network) models and want to evaluate those models, so I'm looking for useful metrics to evaluate RNN models?
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Does the sequence length of a RNN/LSTM have to be the same for the input and output?

I have a question about the input and output data in a RNN or LSTM. A RNN expects a 3-dimensional vector as input of the form (Batch_size, sequence_length_input, features_input) and a 3-dimensional ...
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RCNN to predict sequence of images (video frames)?

In the following work the authors apply a convolutional recurrent neural network (RNN) to predict the spatiotemporal evolution of microstructure represented by 2D image sequences. In particular, they ...
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Non-linear solver with RNN for MPC

Is it possible to use a non-linear solver to optimize the output of a recurrent neural network (RNN) by using a solver to find the optimal RNN inputs? For example, I want to optimize a RNN to a cost ...
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Dual Branch Recurrent Neural Network, what is the correct architecture and can I turn off one branch?

Let's suppose I want to predict the daily consumption of apples in the next 30 days of a person and I have, as input, the historical information about the past 60 days and the demographic information ...
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Question about Reservoir computing (echo state networks)

Does anyone know why reservoir computing is only applied to time-series (data with temporal structure) and has not been applied instead of usual ANN for non-temporal problems? According to (http://...
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Multivariate RNN/LSTM architecture for optimizing one input variable

Let $x = [x_1, x_2, x_3]$ and $y = y$ where all variables in $x$ correlates highly with $y$ and there could also be some crosscorrelation within the set of variables in $x$. The data takes the form of ...
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Use Lstm for classifying problem

i have a dataset of 10000 event with 16 feature, and a vector of dimension 10000 that represent the label of each event; for what i understand is a classification problem but it's required to use a ...
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external input and Reinforcement Learning

Is there an RL method which in it the next state depends on the "current action" and "current state" AND an "External Input"?
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Back propagation process of RNN?

I'm learning how to use the Recurrent Neural Network model (RNN). I'm not entirely sure about the feed-forward procedure in RNN. It includes, for example, input, hidden state, and output. As far as I ...
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Hopfield Network python implementation, Network doesn't converge to one of the learned patterns

I'm trying to implement a Hopfield Network in python using the NumPy library. The network has 2500 nodes (50 height x 50 width). The network learns 10 patterns from images of size 50x50 stored in &...
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How to put marker on time series training set

My input is this picture And I would like to put markers on it and use time series with markers as a label Two picture are not scaled. Main point is I would like to train RNN classifier and let it be ...
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Problems to understand how to create the input data for time series forecasting with a recurrent neural network in Keras

I just started to use recurrent neural networks (RNN) with Keras for time-series forecasting and I found this tutorial Forecasting with RNN. I have difficulties understanding how to build the training ...
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