Learning to Push the Limits of Efficient FFT-Based Image Deconvolution. - Jakob Kruse; Carsten Rother; Uwe Schmidt 001 (ICCV, 2017)

Analyzing Inverse Problems with Invertible Neural Networks. - Lynton Ardizzone; Jakob Kruse; Sebastian J. Wirkert; Daniel Rahner; Eric W. Pellegrini; Ralf S. Klessen; Lena Maier-Hein; Carsten Rother; Ullrich Köthe (CoRR, 2018)

Analyzing Inverse Problems with Invertible Neural Networks. - Lynton Ardizzone; Jakob Kruse; Carsten Rother; Ullrich Köthe (ICLR (Poster), 2019)

Uncertainty-aware performance assessment of optical imaging modalities with invertible neural networks. - Tim J. Adler; Lynton Ardizzone; Anant Suraj Vemuri; Leonardo Ayala; Janek Gröhl; Thomas Kirchner; Sebastian J. Wirkert; Jakob Kruse; Carsten Rother; Ullrich Köthe; Lena Maier-Hein (Int. J. Comput. Assist. Radiol. Surg., 2019)

HINT: Hierarchical Invertible Neural Transport for General and Sequential Bayesian inference. - Gianluca Detommaso; Jakob Kruse; Lynton Ardizzone; Carsten Rother; Ullrich Köthe; Robert Scheichl (CoRR, 2019)

Guided Image Generation with Conditional Invertible Neural Networks. - Lynton Ardizzone; Carsten T. Lüth; Jakob Kruse; Carsten Rother; Ullrich Köthe (CoRR, 2019)

Conditional Invertible Neural Networks for Diverse Image-to-Image Translation. - Lynton Ardizzone; Jakob Kruse; Carsten T. Lüth; Niels Bracher; Carsten Rother; Ullrich Köthe (GCPR, 2020)

Technical report: Training Mixture Density Networks with full covariance matrices. - Jakob Kruse (CoRR, 2020)

HINT: Hierarchical Invertible Neural Transport for Density Estimation and Bayesian Inference. - Jakob Kruse; Gianluca Detommaso; Ullrich Köthe; Robert Scheichl (AAAI, 2021)

Benchmarking Invertible Architectures on Inverse Problems. - Jakob Kruse; Lynton Ardizzone; Carsten Rother; Ullrich Köthe (CoRR, 2021)

Towards Learned Emulation of Interannual Water Isotopologue Variations in General Circulation Models. - Jonathan Wider; Jakob Kruse; Nils Weitzel; Janica C. Bühler; Ullrich Köthe; Kira Rehfeld (CoRR, 2023)