I have a dataset containing 1000 examples where each example has 5 features (a,b,c,d,e). I want to feed 7 examples to an LSTM so it predicts the feature (a) of the 8th day. Reading Pytorchs docume...

I am confused between how to correctly use dropout with RNN in keras, specifically with GRU units. The keras documentation refers to this paper (https://arxiv.org/abs/1512.05287) and I understand t...

I am learning tensorflow2.0 and follow the tutorial. In the rnn example, I found the code: def build_model(vocab_size, embedding_dim, rnn_units, batch_size): model = tf.keras.Sequential([ tf.ker...

I was working with Sequence to Sequence models in Pytorch. Sequence to Sequence Models comprises of an Encoder and a Decoder. The Encoder convert a (batch_size X input_features X num_of_one_hot_en...

In the following example, there are three time series and I want to predict another time series y which is a function of the three. How can I use four inputs to predict the time series where the fo...

I am trying to do multi-class classification with textual data. Problem I am facing that I have unstructured textual data. I'll explain the problem with an example. consider this image for example:...

I can't seem to wrap my head around the difference between return state and return sequence in a keras GRU layer. Since a GRU unit does not have a cell state (it is equal to the ouput), how does r...

I am looking for a way to access the LSTM layer such that the addition and subtraction of a layer are event-driven. So the Layer can be added or subtracted when there is a function trigger. For Ex...

I want to design a single layer RNN in Tensorflow such that last output (y(t-1)) is participated in updating the hidden state. h(t) = tanh(W_{ih} * x(t) + W_{hh} * h(t) + **W_{oh}y(t - 1)**) y(t) ...

The following is self-contained, and when you run it it will: 1. print the loss to verify it's decreasing (learning a sin wave), 2. Check the numeric gradients against my hand-derived gradient ...

In case where suppose I have a trained RNN (e.g. language model), and I want to see what it would generate on its own, how should I feed its output back to its input? I read the following related ...

I'm using Keras to build a LSTM and tuning it by doing gradient descent with an external cost function. So the weights are updated with: weights := weights + alpha* gradient(cost) I know that I ...

This is the API I am looking at, https://pytorch.org/docs/stable/nn.html#gru It outputs: output of shape (seq_len, batch, num_directions * hidden_size) h_n of shape (num_layers * num_directions,...

I am a newbie to LSTM and RNN as a whole, I've been racking my brain to understand what exactly is a timestep. I would really appreciate an intuitive explanation to this

I am new to LSTMs and going through the Understanding Keras LSTMs and had some silly doubts related to a beautiful answer by Daniel Moller. Here are some of my doubts: There are 2 ways specifie...

I am new to Keras and going through the LSTM and its implementation details in Keras documentation. It was going easy but suddenly I came through this SO post and the comment. It has confused me on...

As an introduction to RNN/LSTM (stateless) I'm training a model with sequences of 200 days of previous data (X), including things like daily price change, daily volume change, etc and for the label...

So i was stuck with a question on how to combine a CNN with a RNN in Keras. While posting the question someone pointed me out that this is the correct way to approach the problem. Apparently i just...

I'm building a RNN loosely based on the TensorFlow tutorial. The relevant parts of my model are as follows: input_sequence = tf.placeholder(tf.float32, [BATCH_SIZE, TIME_STEPS, PIXEL_COUNT + AUX_...

So I am trying to train a simple recurrent network to detect a "burst" in an input signal. The following figure shows the input signal (blue) and the desired (classification) output of the RNN, sho...

In Andrew Ng's Deep Learning Coursera classes, there's an assignment on trigger word detection (example, not mine: jupyter notebook). In the assignment, they simply provided the trained model beca...

I'm trying out the Keras package in R by doing this tutorial about forecasting the temperature. However, the tutorial has no explanation on how to predict with the trained RNN model and I wonder ho...

I was trying to use an RNN (specifically, LSTM) for sequence prediction. However, I ran into an issue with variable sequence lengths. For example, sent_1 = "I am flying to Dubain" sent_2 = "I was ...

I'm building an RNN LSTM network to classify texts based on the writers' age (binary classification - young / adult). Seems like the network does not learn and suddenly starts overfitting: Red: ...

I have been developing feedforward neural networks (FNNs) and recurrent neural networks (RNNs) in Keras with structured data of the shape [instances, time, features], and the performance of FNNs an...