no code implementations • 30 Jan 2024 • Linus Bleistein, Van-Tuan Nguyen, Adeline Fermanian, Agathe Guilloux
We consider the task of learning individual-specific intensities of counting processes from a set of static variables and irregularly sampled time series.
no code implementations • 26 May 2023 • Linus Bleistein, Agathe Guilloux
Neural Controlled Differential Equations (NCDEs) are a state-of-the-art tool for supervised learning with irregularly sampled time series (Kidger, 2020).
1 code implementation • 27 Jan 2023 • Linus Bleistein, Adeline Fermanian, Anne-Sophie Jannot, Agathe Guilloux
We address the problem of learning the dynamics of an unknown non-parametric system linking a target and a feature time series.