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Non-Euclidean motion planning with graphs of geodesically convex sets
Computing optimal, collision-free trajectories for high-dimensional systems is a challenging
and important problem. Sampling-based planners struggle with the dimensionality, whereas …
and important problem. Sampling-based planners struggle with the dimensionality, whereas …
Manifold learning by mixture models of VAEs for inverse problems
Representing a manifold of very high-dimensional data with generative models has been
shown to be computationally efficient in practice. However, this requires that the data …
shown to be computationally efficient in practice. However, this requires that the data …
Manifold Learning and Sparsity Priors for Inverse Problems
S Sciutto - 2024 - tesidottorato.depositolegale.it
In this thesis we investigate two distinct regularizing approaches for solving inverse
problems. The first approach involves assuming that the unknown belongs to a manifold …
problems. The first approach involves assuming that the unknown belongs to a manifold …
Atlas flow: compatible local structures on the manifold
In this paper, we focus on the intersections of a manifold's local structures to analyze the
global structure of a manifold. We obtain local regions on data manifolds such as the latent …
global structure of a manifold. We obtain local regions on data manifolds such as the latent …