A normalizing flow models a complex probability density as an invertible
transformation of a simple base density. Flows based on either coupling or
autoregressive transforms both offer exact density evaluation an
Flow-based deep generative models can be used for novelty detection in time series data and outperform traditional methods like the Local Outlier Factor.