Author

T. Helin

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#machine learning Open access Feb 2026

Score-based diffusion models for severely ill-posed problems in diffuse optical tomography

It is shown that both the model-based approach and approximate diffusion-based sampling degrade significantly in the presence of limited-view geometry and real experimental data, whereas UCoS yields more accurate reconstructions.

Fabian Schneider, Meghdoot Mozumder, Konstantin Tamarov et al. · Inverse Problems and Imaging · 1 citation

Preprint Jul 2026

Statistical inverse learning and $\ell^1$-regularization

It is proved that membership in the approximation space $k_t$ is equivalent to polynomial decay of the best $n$-term approximation error, which is equivalent to polynomial decay of the best $n$-term approximation error.

Abhishake Rastogi, T. Bubba, T. Helin et al. · 0 citations