TrajectoryNet: A Dynamic Optimal Transport Network for Modeling Cellular Dynamics.

ABSTRACT: It is increasingly common to encounter data from dynamic processes captured by static cross-sectional measurements over time, particularly in biomedical settings. Recent attempts to model individual trajectories from this data use optimal transport to create pairwise matchings between time points. However, these methods cannot model continuous dynamics and non-linear paths that entities can take in these systems. To address this issue, we establish a link between continuous normalizing flows and dynamic optimal transport, that allows us to model the expected paths of points over time. Continuous normalizing flows are generally under constrained, as they are allowed to take an arbitrary path from the source to the target distribution. We present TrajectoryNet, which controls the cont

SUBMITTER: Tong A 

PROVIDER: S-EPMC8320749 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature