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TILT: topological interface recovery in limited-angle tomography
A novel reconstruction method is introduced for the severely ill-posed inverse problem of limited-angle tomography.
Deep Invertible Approximation of Topologically Rich Maps between Manifolds
By exploiting the topological parallels between locally bilipschitz maps, covering spaces, and local homeomorphisms, and by using universal approximation arguments from machine learning, we find that a novel network of the form $\mathcal{T} \circ p \circ \mathcal{E}$, where $\mathcal{E}$ is an injective network, $p$ a fixed coordinate projection, and $\mathcal{T}$ a bijective network, is a universal approximator of local diffeomorphisms between compact smooth submanifolds embedded in $\mathbb{R}^n$.
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