Data Science

Questions tagged [gru]

Ask Question

The tag has no usage guidance.

21 questions
Newest
Active
Bountied
Unanswered
Filter by
Sorted by
Tagged with
0
votes
3answers
56 views

Converting a speech recognition model from CNNs to GRUs

I am trying to convert the simple audio recognition example from TensorFlow to use GRUs instead of CNNs. The idea is to classify an audio clip onto a set of 8 labels: ...
0
votes
0answers
15 views

What does the inital_state parameter in the GRU call arguments do?

Does the inital_state parameter in the GRU call arguments, specify the inital state of the hidden state, that is, $h_t$ or the weights?
0
votes
1answer
22 views

How is the hidden state of a GRU initialized

This is a GRU. Now, what will be the value of $h_t$, at $t$=$0$. That is, what will be the value of the hidden state at just the starting?
0
votes
0answers
53 views

What is the time complexity for training a gated recurrent unit (GRU) neural network using back-propagation through time?

Let us assume we have a GRU network containing $H$ layers to process a training dataset with $K$ tuples, $I$ features, and $H_i$ nodes in each layer. I have a pretty basic idea how the complexity of ...
0
votes
0answers
20 views

How to get the weight matrices of intermediate layers in bidirectional recurrent neural networks?

I am a newbie in deep learning. I have a doubt regarding the training procedure of bidirectional recurrent neural networks using backpropagation through time. Following the original paper for ...
0
votes
0answers
33 views

Google Trax's GRU layer

I am learning about Trax for the implementation of GRU and LSTMs. Their documentation says that a GRU layer in Trax can only accept a number of hidden units equal to the number of elements in the ...
0
votes
0answers
13 views

Time duration weighted recurrent neural network

Suppose the input time-series feature is $\vec{X}=[\mathbf{x_0},\mathbf{x_1},...\mathbf{x_T}]$, where at each time step $t\in[0,...,T]$, feature $\mathbf{x_t}$ is a vector with dimension $n$. Typical ...
0
votes
0answers
15 views

TCNN vs Conv1D+LSTM

I was reading a bit about TCNN, just wanted to ask if someone has worked with it, can you tell that which is better and Why? 1d Conv + LSTM/GRU or TCNN.
0
votes
1answer
38 views

Why is the variance of my model predictions much smaller than the training data?

I trained a GRU model on some data and then created a bunch of predictions on a test set. The predictions are really bad, as indicated by a near zero R2 score. I notice that the variance of the model ...
0
votes
1answer
28 views

LSTM / GRU weights during test time

I am working on a historic time series dataset and using RNN, LSTM, GRU models, and I didn't find an answer if in test time, the h (or h, c) weights should be zeors for each batch? If the weights ...
2
votes
1answer
27 views

GRU and LSTM does not “take risk” predicting

I tested LSTM and GRU models to predict the exchange rate between currencies. I do not take the raw price but a the delta with the previous day, so the data is stationnary around zero. My problem is ...
2
votes
0answers
56 views

Custom GRU With 3D Spatial Convolution Layer In Keras

I am trying to implement a custom GRU model that is shown in this paper 3D-R2N2 The GRU pipeline looks like: The original implementation is theano based and I am trying to apply the model in tf2/...
1
vote
1answer
559 views

How to add a Decoder & Attention Layer to Bidirectional Encoder with tensorflow 2.0

I am a beginner in machine learning and I'm trying to create a spelling correction model that spell checks for a small amount of vocab (approximately 1000 phrases). Currently, I am refering to the ...
1
vote
0answers
34 views

LSTM / GRU prediction with hidden state?

I am trying to predict a value based on time series by series of 24 periods (the 25th period) While training I have a validation set with I babysit the training (RMSE) and each epoch, eval the ...
1
vote
1answer
109 views

Using GRU with FeedForward layers in Python

I'm trying to reproduce the codes in this paper here for the multi-labeling problem (11 classes), which is using ...
1
vote
1answer
93 views

Keras RNN (batch_size

I created an RNN model for text classification with the LSTM layer, but when I put the batch_size in the fit method, my model trained on the whole batch instead of just the mini-batch _size. This also ...
3
votes
1answer
1k views

TensorFlow / Keras: What is stateful = True in LSTM layers?

Could you elaborate on this argument? I found the brief explanation from the docs unsatisfying: stateful: Boolean (default False). If True, the last state for each sample at index i in a batch will ...
2
votes
1answer
179 views

Impact of varying sequence length in ensemble GRU model

I am using ensemble gru for my project and keeping different cell sizes for different models !For example, first gru model is of size 16 and the second is of 8 and 4 for the third model. The model is ...
2
votes
0answers
26 views

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 ...
2
votes
0answers
56 views

GRU learns small-scale features, but misses large scales

Playing around with weather data, I have set up a simple RNN with one layer of GRUs. It is trained to recover the temperature of the next day, given weather data of the last 5 days, each with 1-hour ...
143
votes
6answers
124k views

When to use GRU over LSTM?

The key difference between a GRU and an LSTM is that a GRU has two gates (reset and update gates) whereas an LSTM has three gates (namely input, output and forget gates). Why do we make use of GRU ...