A Generative Variational Model for Inverse Problems in Imaging. - Andreas Habring; Martin Holler (SIAM J. Math. Data Sci., 2022)

Probabilistic Modeling of Chronological Dates to Serve Machines and Scholars. - Andreas Habring; Anguelos Nicolaou; Daniel Luger; Florian Atzenhofer-Baumgartner; Florian Lamminger; Franziska Decker; Sandy Aoun; Tamás Kovács; Georg Vogeler; Martin Holler (DH, 2023)

A Note on the Regularity of Images Generated by Convolutional Neural Networks. - Andreas Habring; Martin Holler (SIAM J. Math. Data Sci., 2023)

Ergodicity of Langevin Dynamics and its Discretizations for Non-smooth Potentials. - Lorenz Fruehwirth; Andreas Habring (CoRR, 2024)

Subgradient Langevin Methods for Sampling from Nonsmooth Potentials. - Andreas Habring; Martin Holler; Thomas Pock (SIAM J. Math. Data Sci., 2024)

Unsupervised Energy Disaggregation Via Convolutional Sparse Coding. - Christian Aarset; Andreas Habring; Martin Holler; Mario Mitter (IEEE Trans. Consumer Electron., 2024)

Posterior-Variance-Based Error Quantification for Inverse Problems in Imaging. - Dominik Narnhofer; Andreas Habring; Martin Holler; Thomas Pock (SIAM J. Imaging Sci., 2024)

Diffusion at Absolute Zero: Langevin Sampling Using Successive Moreau Envelopes. - Andreas Habring; Alexander Falk; Thomas Pock (SSP, 2025)

The Gaussian Latent Machine: Efficient Prior and Posterior Sampling for Inverse Problems. - Muhamed Kuric; Martin Zach; Andreas Habring; Michael Unser; Thomas Pock (CoRR, 2025)