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Found 3 papers, 1 papers with code
Dynamical Survival Analysis with Controlled Latent States
We consider the task of learning individual-specific intensities of counting processes from a set of static variables and irregularly sampled time series.
On the Generalization and Approximation Capacities of Neural Controlled Differential Equations
Neural Controlled Differential Equations (NCDEs) are a state-of-the-art tool for supervised learning with irregularly sampled time series (Kidger, 2020).
Learning the Dynamics of Sparsely Observed Interacting Systems
We address the problem of learning the dynamics of an unknown non-parametric system linking a target and a feature time series.
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