Web: http://arxiv.org/abs/2206.08311

June 17, 2022, 1:12 a.m. | Nabeel Seedat, Fergus Imrie, Alexis Bellot, Zhaozhi Qian, Mihaela van der Schaar

stat.ML updates on arXiv.org arxiv.org

Estimating counterfactual outcomes over time has the potential to unlock
personalized healthcare by assisting decision-makers to answer ''what-iF''
questions. Existing causal inference approaches typically consider regular,
discrete-time intervals between observations and treatment decisions and hence
are unable to naturally model irregularly sampled data, which is the common
setting in practice. To handle arbitrary observation patterns, we interpret the
data as samples from an underlying continuous-time process and propose to model
its latent trajectory explicitly using the mathematics of controlled
differential …

arxiv lg modeling neural time

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