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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7
votes
1answer
6k views

How does LSTM in deep reinforcement learning differ from experience replay?

In the paper Deep Recurrent Q-Learning for Partially Observable MDPs, the author processed the Atari game frames with an LSTM layer at the end. My questions are: How does this method differ from the ...
28
votes
4answers
41k views

How to select number of hidden layers and number of memory cells in an LSTM?

I am trying to find some existing research on how to select the number of hidden layers and the size of these of an LSTM-based RNN. Is there an article where this problem is being investigated, i.e., ...
6
votes
1answer
2k views

Where can I find the original paper that introduced RNNs?

I was able to find the original paper on LSTM, I was not able to find the paper that introduced "vanilla" RNNs. Where can I find it?
1
vote
2answers
131 views

Are artificial networks based on the perceptron design inherently limiting?

At the time when the basic building blocks of machine learning (the perceptron layer and the convolution kernel) were invented, the model of the neuron in the brain taught at the university level was ...
3
votes
0answers
107 views

What can be considered a deep recurrent neural network?

In the paper Deep Recurrent Q-Learning for Partially Observable MDPs, the DRQN is described as DQN with the first post-convolutional fully-connected layer replaced by a recurrent LSTM. I have DQN ...
1
vote
2answers
87 views

What are some examples of LSTM architectures?

I've been doing some class assignments recently on building various neural networks. For convolutional networks, there are several well-known architectures such as LeNet, VGG etc. Such "classic" ...
0
votes
0answers
19 views

Why is the value range of my LSTM model's prediction different from my test labels?

I am using LSTM to do time-series anomaly detection. The data is an hourly sensor input across multiple years (i.e. the global_active_energy attribute of the dataset from https://www.kaggle.com/uciml/...