Popular deep learning architectures that can be used in an anomaly detection framework include: Autoencoder ... Recurrent Neural Network (e.g. LSTM, GRU, Attention), however, can handle temporal ...

The demo program presented in this article uses image data, but the autoencoder anomaly detection technique can work with any type of data. The demo begins by creating a Dataset object that stores the ...

In the paper, the researchers propose TadGAN: an “unsupervised anomaly detection approach built on Generative ... six deep learning methods (HTM, LSTM, LSTM AutoEncoder, MAD-GAN, Microsoft Azure ...

The demo program presented in this article uses image data, but the autoencoder anomaly detection technique can work with any type of data. The demo begins by creating a Dataset object that stores the ...