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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 decoder.

The Data Science Lab Data Dimensionality Reduction Using a Neural Autoencoder with C# Dr. James McCaffrey of Microsoft Research presents a full-code, step-by-step tutorial on creating an approximation ...

The concept of autoencoder was originally proposed by LeCun in 1987, early works on autoencoder were used for dimensionality reduction or feature learning. Recently, with the popularity of deep ...

We propose a method that uses kernel method-based algorithms to implement an autoencoder. Deep learning-based algorithms have two characteristics, one is the high level data abstraction, the other is ...

That said, applying a neural autoencoder anomaly detection system to tabular data is typically the best way to start. A limitation of the autoencoder architecture presented in this article is that it ...