Autoregressive

Flow-Based Models for Density Estimation with TensorFlowFig: From random to not-so-random! Source: Author’s Notebook (see References below).Previously we went through the details of the mathematics behind Normalizing Flows and some examples of transforming probability distributions. Here we combine all these concepts to understand Autoregressive Flows and how to implement them using TensorFlow Probability library. What can you expect from this post —Why Triangular Matrices are crucial for Autoregressive Flows?Basic…

Pipelines can get complicated at times. Poland 2022. (Photo by the author).Autoregressive models are among the “more difficult” to implement when it comes to data preparation. As the models are expected to yield daily or hourly predictions, the datasets themselves are expected to grow and expand with every new observation requiring the models to undergo regular retraining. Consequently, handling the data becomes a highly dynamic process where one has to be extra careful to ensure that no data leakage is present at any…