Discovering group dynamics in synchronous time series via hierarchical recurrent switching-state models

no code implementations • 26 Jan 2024 • Michael Wojnowicz, Preetish Rath, Eric Miller, Jeffrey Miller, Clifford Hancock, Meghan O'Donovan, Seth Elkin-Frankston, Thaddeus Brunye, Michael C. Hughes

Our hierarchical switching recurrent dynamical models can be learned via closed-form variational coordinate ascent updates to all latent chains that scale linearly in the number of individual time series.

Time Series

Flexible Models for Microclustering with Application to Entity Resolution

no code implementations • NeurIPS 2016 • Giacomo Zanella, Brenda Betancourt, Hanna Wallach, Jeffrey Miller, Abbas Zaidi, Rebecca C. Steorts

Most generative models for clustering implicitly assume that the number of data points in each cluster grows linearly with the total number of data points.

Clustering Entity Resolution

Microclustering: When the Cluster Sizes Grow Sublinearly with the Size of the Data Set

no code implementations • 2 Dec 2015 • Jeffrey Miller, Brenda Betancourt, Abbas Zaidi, Hanna Wallach, Rebecca C. Steorts

Most generative models for clustering implicitly assume that the number of data points in each cluster grows linearly with the total number of data points.

Clustering Entity Resolution