Jakob Kruse

Doctoral student at Visual Learning Lab Heidelberg
Mathematikon B, room A117

Email: jakob.kruse (at) iwr.uni-heidelberg.de
Phone: +49 6221 54 14887 (shared)
Address:
IWR, Uni Heidelberg
Berliner Straße 43
69120 Heidelberg

Publications

Lynton Ardizzone, Carsten Lüth, Jakob Kruse, Carsten Rother, Ullrich Köthe. Guided Image Generation with Conditional Invertible Neural Networks. arXiv:1907.02392, July 2019.
[arXiv page]

Jakob Kruse, Lynton Ardizzone, Carsten Rother, Ullrich Köthe. Benchmarking Invertible Architectures on Inverse Problems. First Workshop on Invertible Neural Networks and Normalizing Flows (ICML 2019), Long Beach, USA, June 2019.
[Paper] [Poster]

Tim J Adler, Lynton Ardizzone, Anant Vemuri, Leonardo Ayala, Janek Gröhl, Thomas Kirchner, Sebastian Wirkert, Jakob Kruse, Carsten Rother, Ullrich Köthe, Lena Maier-Hein. Uncertainty-Aware Performance Assessment of Optical Imaging Modalities with Invertible Neural Networks. International Journal of Computer Assisted Radiology and Surgery (IJCARS), 14:997, June 2019.
[SpringerLink]

Lynton Ardizzone, Jakob Kruse, Sebastian Wirkert, Daniel Rahner, Eric W. Pellegrini, Ralf S. Klessen, Lena Maier-Hein, Carsten Rother, Ullrich Köthe. Analyzing Inverse Problems with Invertible Neural Networks. International Conference on Learning Representations (ICLR), New Orleans, USA, May 2019.
[OpenReview page] [Poster] [Code]

Jakob Kruse, Carsten Rother and Uwe Schmidt. Learning to Push the Limits of Efficient FFT-based Image Deconvolution. IEEE International Conference on Computer Vision (ICCV), Venice, Italy, October 2017.
Spotlight presentation.
[Paper] [Supplement] [Poster] [Spotlight Talk] [Code]

Talks

Invertible Neural Networks as a tool for ill-posed inverse problems. Bremen, September 2019.
[Slides]

Teaching

Bomberman Multi-agent Reinforcement Learning Environment. For Fundamentals of Machine Learning WS 18/19.
[Framework] [2019 tournament results]

Theses

Comparison of Learned Inference Approaches for Image Restoration. Master’s Thesis, September 2016.
Graded 1.0
[Thesis] [Slides]

Steganalyse einer Erweiterung des steganographischen Algorithmus HUGO. Bachelor’s Thesis, April 2013.
Graded 1.2
[Thesis] (German)

Misc

Super-Resolution with Regression Tree Fields. Lab Course, May 2015.
[Report]

Looped mathsy animations. Just a hobby 🙂
[Gallery] [Instagram] [Partial code]