most citedDeep learning and differential equations for modeling changes in individual-level latent dynamics between observation periods

2 citations · 2 across the 1 of their papers we have counts for

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1 paper

stat.ML2022★ 2 cited

Deep learning and differential equations for modeling changes in individual-level latent dynamics between observation periods

Göran Köber, Raffael Kalisch, Lara Puhlmann +3

When modeling longitudinal biomedical data, often dimensionality reduction as well as dynamic modeling in the resulting latent representation is needed. This can be achieved by art…