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Inverse problems involve for example reconstruction of an object based on physical measurements and finding a best model/parameters out of a family given observed data. Typically the corresponding "forward" problems are well-posed and can be solved straightforwardly, while the inverse problems are often ill-posed. Not to be confused with the (inverse) tag.

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Approximating Uniform Distribution with Mixture of Gaussians

My suggestion would be to first determine a 3D delaunay triangulation of the point set; then determine a B-Spline basis on that triangulation and finally calculate for each B-Spline basis the best-app …
Manfred Weis's user avatar
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2 votes
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inverse interpolation

After having calculated an "explicit" interpolating function $f:\mathbb{R}^m\rightarrow \mathbb{R}^n$, satisfying $y_i=f (x_i)$, you can calculate the local inverse via evaluation of the implicit tayl …
Manfred Weis's user avatar
  • 13.2k
8 votes

What's that shape? Inferring a 3D shape from random shadows

Shape-reconstruction from shadows will definitely be impossible for "modified convex" polyhedra, that are topologically equivalent to a sphere and can be generated from a corresponding truly convex po …
Manfred Weis's user avatar
  • 13.2k