Uncertainty quantification for sparse Fourier recovery. - Frederik Hoppe; Felix Krahmer; Claudio Mayrink Verdun; Marion I. Menzel; Holger Rauhut (CoRR, 2022)

High-Dimensional Confidence Regions in Sparse MRI. - Frederik Hoppe; Felix Krahmer; Claudio Mayrink Verdun; Marion I. Menzel; Holger Rauhut (ICASSP, 2023)

Uncertainty Quantification For Learned ISTA. - Frederik Hoppe; Claudio Mayrink Verdun; Hannah Laus; Felix Krahmer; Holger Rauhut (MLSP, 2023)

Imaging with Confidence: Uncertainty Quantification for High-Dimensional Undersampled MR Images. - Frederik Hoppe; Claudio Mayrink Verdun; Hannah Laus; Sebastian Endt; Marion I. Menzel; Felix Krahmer; Holger Rauhut (ECCV (78), 2024)

Non-Asymptotic Uncertainty Quantification in High-Dimensional Learning. - Frederik Hoppe; Claudio Mayrink Verdun; Hannah Laus; Felix Krahmer; Holger Rauhut (NeurIPS, 2024)

With or Without Replacement? Improving Confidence in Fourier Imaging. - Frederik Hoppe; Claudio Mayrink Verdun; Felix Krahmer; Marion I. Menzel; Holger Rauhut (CoRR, 2024)

Generating Synthetic Relational Tabular Data via Structural Causal Models. - Frederik Hoppe; Astrid Franz; Lars Kleinemeier; Udo Göbel (CoRR, 2025)

Universal Embeddings of Tabular Data. - Astrid Franz; Frederik Hoppe; Marianne Michaelis; Udo Göbel (CoRR, 2025)