A neural ODE latent model regularized with Wasserstein barycentric trajectories improves interpolation and reconstruction of time-evolving images under data scarcity.
SIAM Journal on Imaging Sciences11(1), 94–128 (2018)
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Joint Manifold Learning and Optimal Transport for Dynamic Imaging
A neural ODE latent model regularized with Wasserstein barycentric trajectories improves interpolation and reconstruction of time-evolving images under data scarcity.