What is an LSTM autoencoder? LSTM autoencoder is an encoder that makes use of LSTM encoder-decoder architecture to compress data using an encoder and decode it to retain original structure using a ...

This program attempts to use an LSTM autoencoder to detect anomalies the daily closing prices of the S&P 500 index. The autoencoder is trained exclusively on normal data without anomalies. When new ...

But using autoencoder, which have many variables with strong correlations, is said to cause a decline of detection power. To avoid the above problem, the technique to apply L1 regularization to LSTM ...

In this study, we apply deep learning to extract SESs and develop a novel deep learning network based on geoelectric field characteristics by combining the long short-term memory (LSTM) blocks with an ...

In order to solve the problem, this paper presents a two-stage hierarchical clustering algorithm based on a Long Short Term Memory (LSTM) autoencoder. Firstly, we use LSTM autoencoder to learn the ...

To tackle this problem, we present a long short-term memory-based adversarial variational autoencoder ... common structure of the data shared among subjects, making it suitable for cross-subject ...