Anomaly detection using a deep neural autoencoder is not a well-known technique. An advantage of using a neural technique compared to a standard clustering technique is that neural techniques can ...

Common use-cases include data visualization in a 2D graph (if the data is reduced to just two columns instead of the six columns in the demo), use in machine learning algorithms (such as k-means ...

We introduce unFEAR, Unsupervised Feature Extraction Clustering, to identify economic crisis regimes. Given labeled crisis and non-crisis episodes and the corresponding features values, unFEAR uses ...

Bryan Lim, Stefan Zohren and Stephen Roberts propose a real-time indicator to detect temporary increases in asset co-movements that they call the autoencoder reconstruction ratio (ARR), which measures ...