Fast Convex Relaxations using Graph Discretizations. - Jonas Geiping; Fjedor Gaede; Hartmut Bauermeister; Michael Moeller 001 (BMVC, 2020)

Exploiting the Logits: Joint Sign Language Recognition and Spell-Correction. - Christina Runkel; Stefan Dorenkamp; Hartmut Bauermeister; Michael Möller 001 (ICPR, 2020)

Inverting Gradients - How easy is it to break privacy in federated learning? - Jonas Geiping; Hartmut Bauermeister; Hannah Dröge; Michael Moeller 001 (NeurIPS, 2020)

Deep Optimization Prior for THz Model Parameter Estimation. - Tak Ming Wong; Hartmut Bauermeister; Matthias Kahl; Peter Haring Bolívar; Michael Möller 001; Andreas Kolb 001 (WACV, 2022)

Convergent Data-driven Regularizations for CT Reconstruction. - Samira Kabri; Alexander Auras; Danilo Riccio; Hartmut Bauermeister; Martin Benning; Michael Moeller 001; Martin Burger 001 (CoRR, 2022)

Lifting the Convex Conjugate in Lagrangian Relaxations: A Tractable Approach for Continuous Markov Random Fields. - Hartmut Bauermeister; Emanuel Laude; Thomas Möllenhoff; Michael Möller 001; Daniel Cremers (SIAM J. Imaging Sci., 2022)

Functional lifting, direct approaches and applications of nonconvex optimization in computer vision (Functional Lifting, direkte Ansätze und Anwendungen nichtkonvexer Optimierung in der Bildverarbeitung) - Hartmut Bauermeister (2023)