Computational Modeling of Hierarchically Polarized Groups by Structured Matrix Factorization.

The paper extends earlier work on modeling hierarchically polarized groups on social media. An algorithm is described that 1) detects points of and between groups, and 2) divides them to represent nested patterns of agreement and disagreement given a structural guide. For example, two opposing parties might disagree on core issues.

ControlVAE: Tuning, Analytical Properties, and Performance Analysis.

This paper reviews the novel concept of a controllable variational autoencoder (ControlVAE), discusses its parameter tuning to meet application needs, derives its key analytic properties, and offers useful extensions and applications. ControlVAE is a new variational autoencoder (VAE) framework that combines automatic control theory with the basic VAE to stabilize the KL-divergence of VAE models to a specified value. It leverages a non-linear PI controller, a variant of the proportional-integral-derivative (PID) controller, to dynamically tune the weight of the KL-divergence term in the evidence lower bound (ELBO) using the output KL-divergence as feedback.