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Benchmarking Invertible Architectures on Inverse Problems


Jan 26, 2021
Jakob Kruse, Lynton Ardizzone, Carsten Rother, Ullrich Köthe

* Workshop on Invertible Neural Networks and Normalizing Flows (ICML 2019) 

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Invertible Neural Networks for Uncertainty Quantification in Photoacoustic Imaging


Nov 10, 2020
Jan-Hinrich Nölke, Tim Adler, Janek Gröhl, Lynton Ardizzone, Carsten Rother, Ullrich Köthe, Lena Maier-Hein

* 7 pages, 4 figures, submitted to "Bildverarbeitung f\"ur die Medizin (BVM) 2021" 

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Learning Robust Models Using The Principle of Independent Causal Mechanisms


Oct 14, 2020
Jens Müller, Robert Schmier, Lynton Ardizzone, Carsten Rother, Ullrich Köthe


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Model-based Bayesian inference of disease outbreak dynamics with invertible neural networks


Oct 13, 2020
Stefan T. Radev, Frederik Graw, Simiao Chen, Nico T. Mutters, Vanessa M. Eichel, Till Bärnighausen, Ullrich Köthe


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Model-based Bayesian inference of disease outbreak with invertible neural networks


Oct 01, 2020
Stefan T. Radev, Frederik Graw, Simiao Chen, Nico Mutters, Vanessa Eichel, Till Bärnighausen, Ullrich Köthe


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Generative Classifiers as a Basis for Trustworthy Computer Vision


Jul 29, 2020
Radek Mackowiak, Lynton Ardizzone, Ullrich Köthe, Carsten Rother


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Amortized Bayesian model comparison with evidential deep learning


Apr 25, 2020
Stefan T. Radev, Marco D'Alessandro, Paul-Christian Bürkner, Ulf K. Mertens, Andreas Voss, Ullrich Köthe


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BayesFlow: Learning complex stochastic models with invertible neural networks


Apr 17, 2020
Stefan T. Radev, Ulf K. Mertens, Andreass Voss, Lynton Ardizzone, Ullrich Köthe


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Exact Information Bottleneck with Invertible Neural Networks: Getting the Best of Discriminative and Generative Modeling


Jan 20, 2020
Lynton Ardizzone, Radek Mackowiak, Ullrich Köthe, Carsten Rother


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Disentanglement by Nonlinear ICA with General Incompressible-flow Networks (GIN)


Jan 14, 2020
Peter Sorrenson, Carsten Rother, Ullrich Köthe

* 23 pages, 15 figures, ICLR 2020 

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Out of distribution detection for intra-operative functional imaging


Nov 05, 2019
Tim J. Adler, Leonardo Ayala, Lynton Ardizzone, Hannes G. Kenngott, Anant Vemuri, Beat P. Müller-Stich, Carsten Rother, Ullrich Köthe, Lena Maier-Hein

* Proceedings of the First International Workshop on Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, UNSURE 2019, and the 8th International Workshop on Clinical Image-Based Procedures, CLIP 2019 
* The final authenticated version is available online at https://doi.org/10.1007/978-3-030-32689-0_8 

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Object Segmentation using Pixel-wise Adversarial Loss


Sep 23, 2019
Ricard Durall, Franz-Josef Pfreundt, Ullrich Köthe, Janis Keuper


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Guided Image Generation with Conditional Invertible Neural Networks


Jul 10, 2019
Lynton Ardizzone, Carsten Lüth, Jakob Kruse, Carsten Rother, Ullrich Köthe


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HINT: Hierarchical Invertible Neural Transport for General and Sequential Bayesian inference


May 25, 2019
Gianluca Detommaso, Jakob Kruse, Lynton Ardizzone, Carsten Rother, Ullrich Köthe, Robert Scheichl


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The Mutex Watershed and its Objective: Efficient, Parameter-Free Image Partitioning


Apr 25, 2019
Steffen Wolf, Alberto Bailoni, Constantin Pape, Nasim Rahaman, Anna Kreshuk, Ullrich Köthe, Fred A. Hamprecht


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Uncertainty-aware performance assessment of optical imaging modalities with invertible neural networks


Mar 08, 2019
Tim J. Adler, Lynton Ardizzone, Anant Vemuri, Leonardo Ayala, Janek Gröhl, Thomas Kirchner, Sebastian Wirkert, Jakob Kruse, Carsten Rother, Ullrich Köthe, Lena Maier-Hein

* Accepted at IPCAI 2019 

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Analyzing Inverse Problems with Invertible Neural Networks


Sep 10, 2018
Lynton Ardizzone, Jakob Kruse, Sebastian Wirkert, Daniel Rahner, Eric W. Pellegrini, Ralf S. Klessen, Lena Maier-Hein, Carsten Rother, Ullrich Köthe


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Learned Watershed: End-to-End Learning of Seeded Segmentation


Sep 04, 2017
Steffen Wolf, Lukas Schott, Ullrich Köthe, Fred Hamprecht

* The first two authors contributed equally 

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