Jakob Kruse
Jakob Kruse
Visual Learning Lab, Heidelberg University (HCI/IWR)
Verified email at iwr.uni-heidelberg.de - Homepage
Title
Cited by
Cited by
Year
Analyzing Inverse Problems with Invertible Neural Networks
L Ardizzone, J Kruse, S Wirkert, D Rahner, EW Pellegrini, RS Klessen, ...
arXiv preprint arXiv:1808.04730, 2018
922018
Learning to push the limits of efficient fft-based image deconvolution
J Kruse, C Rother, U Schmidt
Proceedings of the IEEE International Conference on Computer Vision, 4586-4594, 2017
362017
Guided Image Generation with Conditional Invertible Neural Networks
L Ardizzone, C Lüth, J Kruse, C Rother, U Köthe
arXiv preprint arXiv:1907.02392, 2019
232019
Uncertainty-aware performance assessment of optical imaging modalities with invertible neural networks
TJ Adler, L Ardizzone, A Vemuri, L Ayala, J Gröhl, T Kirchner, S Wirkert, ...
International journal of computer assisted radiology and surgery, 1-11, 2019
92019
Benchmarking Invertible Architectures on Inverse Problems
J Kruse, L Ardizzone, C Rother, U Köthe
Workshop on Invertible Neural Networks and Normalizing Flows, International …, 2019
42019
Hint: Hierarchical invertible neural transport for general and sequential bayesian inference
G Detommaso, J Kruse, L Ardizzone, C Rother, U Köthe, R Scheichl
stat 1050, 25, 2019
32019
Technical report: Training Mixture Density Networks with full covariance matrices
J Kruse
arXiv preprint arXiv:2003.05739, 2020
2020
Conditional Invertible Neural Networks for Guided Image Generation
L Ardizzone, C Lüth, J Kruse, C Rother, U Köthe
2019
HINT: Hierarchical Invertible Neural Transport for Density Estimation and Bayesian Inference
J Kruse, G Detommaso, R Scheichl, U Köthe
arXiv preprint arXiv:1905.10687, 2019
2019
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Articles 1–9