no code implementations • 8 Feb 2024 • Maksim Sinelnikov, Manuel Haussmann, Harri Lähdesmäki
Longitudinal data are important in numerous fields, such as healthcare, sociology and seismology, but real-world datasets present notable challenges for practitioners because they can be high-dimensional, contain structured missingness patterns, and measurement time points can be governed by an unknown stochastic process.