Ullrich Köthe

167 papers A* 22A 4B 3C 1Misc 1Journal 78Unranked 55

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Breaking the Simplification Bottleneck in Amortized Neural Symbolic Regression. CoRR Paul Saegert, Ullrich Köthe
2026	J	`jnl`	From Core to Detail: Unsupervised Disentanglement with Entropy-Ordered Flows. CoRR Daniel Galperin, Ullrich Köthe
2026	J	`jnl`	Show Me What You Don't Know: Efficient Sampling from Invariant Sets for Model Validation. CoRR Armand Rousselot, Joran Wendebourg, Ullrich Köthe
2025	A	`conf`	Analyzing Generative Models by Manifold Entropic Metrics. AISTATS Daniel Galperin, Ullrich Köthe
2025	J	`jnl`	Application-driven validation of posteriors in inverse problems. Medical Image Anal. Tim J. Adler, Jan-Hinrich Nölke, Annika Reinke, Minu Dietlinde Tizabi, Sebastian Gruber, Dasha Trofimova, Lynton Ardizzone, Paul F. Jaeger, Florian Buettner, Ullrich Köthe, Lena Maier-Hein
2025	J	`jnl`	Beyond Diagonal Covariance: Flexible Posterior VAEs via Free-Form Injective Flows. CoRR Peter Sorrenson, Lukas Lührs, Hans Olischläger, Ullrich Köthe
2025	J	`jnl`	Diffusion Models in Simulation-Based Inference: A Tutorial Review. CoRR Jonas Arruda, Niels Bracher, Ullrich Köthe, Jan Hasenauer, Stefan T. Radev
2025	A*	`conf`	Learning Distances from Data with Normalizing Flows and Score Matching. ICML Peter Sorrenson, Daniel Behrend-Uriarte, Christoph Schnörr, Ullrich Köthe
2025	J	`jnl`	OOD Detection with immature Models. CoRR Behrooz Montazeran, Ullrich Köthe
2025	J	`jnl`	Split-Flows: Measure Transport and Information Loss Across Molecular Resolutions. CoRR Sander Hummerich, Tristan Bereau, Ullrich Köthe
2025	A	`conf`	TRADE: Transfer of Distributions between External Conditions with Normalizing Flows. AISTATS Stefan Wahl, Armand Rousselot, Felix Draxler, Ullrich Köthe
2024	J	`jnl`	Analyzing Generative Models by Manifold Entropic Metrics. CoRR Daniel Galperin, Ullrich Köthe
2024	A*	`conf`	Consistency Models for Scalable and Fast Simulation-Based Inference. NeurIPS Marvin Schmitt, Valentin Pratz, Ullrich Köthe, Paul-Christian Bürkner, Stefan T. Radev
2024	J	`jnl`	DALSA: Domain Adaptation for Supervised Learning From Sparsely Annotated MR Images. CoRR Michael Götz, Christian Weber, Franciszek Binczyk, Joanna Polanska, Rafal Tarnawski, Barbara Bobek-Billewicz, Ullrich Köthe, Jens Kleesiek, Bram Stieltjes, Klaus H. Maier-Hein
2024	J	`jnl`	Deciphering the Definition of Adversarial Robustness for post-hoc OOD Detectors. CoRR Peter Lorenz, Mario Fernandez, Jens Müller, Ullrich Köthe
2024	J	`jnl`	Detecting Model Misspecification in Amortized Bayesian Inference with Neural Networks: An Extended Investigation. CoRR Marvin Schmitt, Paul-Christian Bürkner, Ullrich Köthe, Stefan T. Radev
2024	A	`conf`	Free-form Flows: Make Any Architecture a Normalizing Flow. AISTATS Felix Draxler, Peter Sorrenson, Lea Zimmermann, Armand Rousselot, Ullrich Köthe
2024	J	`jnl`	Learning Distances from Data with Normalizing Flows and Score Matching. CoRR Peter Sorrenson, Daniel Behrend-Uriarte, Christoph Schnörr, Ullrich Köthe
2024	A*	`conf`	Learning Distributions on Manifolds with Free-Form Flows. NeurIPS Peter Sorrenson, Felix Draxler, Armand Rousselot, Sander Hummerich, Ullrich Köthe
2024	A*	`conf`	Leveraging Self-Consistency for Data-Efficient Amortized Bayesian Inference. ICML Marvin Schmitt, Desi R. Ivanova, Daniel Habermann, Ullrich Köthe, Paul-Christian Bürkner, Stefan T. Radev
2024	A*	`conf`	Lifting Architectural Constraints of Injective Flows. ICLR Peter Sorrenson, Felix Draxler, Armand Rousselot, Sander Hummerich, Lea Zimmermann, Ullrich Köthe
2024	J	`jnl`	On the Universality of Coupling-based Normalizing Flows. CoRR Felix Draxler, Stefan Wahl, Christoph Schnörr, Ullrich Köthe
2024	A*	`conf`	On the Universality of Volume-Preserving and Coupling-Based Normalizing Flows. ICML Felix Draxler, Stefan Wahl, Christoph Schnörr, Ullrich Köthe
2024	—	`ed.`	Pattern Recognition - 45th DAGM German Conference, DAGM GCPR 2023, Heidelberg, Germany, September 19-22, 2023, Proceedings DAGM Ullrich Köthe, Carsten Rother
2024	J	`jnl`	Sensitivity-Aware Amortized Bayesian Inference. Trans. Mach. Learn. Res. Lasse Elsemüller, Hans Olischläger, Marvin Schmitt, Paul-Christian Bürkner, Ullrich Köthe, Stefan T. Radev
2024	J	`jnl`	TRADE: Transfer of Distributions between External Conditions with Normalizing Flows. CoRR Stefan Wahl, Armand Rousselot, Felix Draxler, Ullrich Köthe
2023	J	`jnl`	A Review of Change of Variable Formulas for Generative Modeling. CoRR Ullrich Köthe
2023	J	`jnl`	Amortized Bayesian Model Comparison With Evidential Deep Learning. IEEE Trans. Neural Networks Learn. Syst. Stefan T. Radev, Marco D'Alessandro, Ulf K. Mertens, Andreas Voss, Ullrich Köthe, Paul-Christian Bürkner
2023	J	`jnl`	Application-driven Validation of Posteriors in Inverse Problems. CoRR Tim J. Adler, Jan-Hinrich Nölke, Annika Reinke, Minu Dietlinde Tizabi, Sebastian Gruber, Dasha Trofimova, Lynton Ardizzone, Paul F. Jaeger, Florian Büttner, Ullrich Köthe, Lena Maier-Hein
2023	J	`jnl`	BayesFlow: Amortized Bayesian Workflows With Neural Networks. CoRR Stefan T. Radev, Marvin Schmitt, Lukas Schumacher, Lasse Elsemüller, Valentin Pratz, Yannik Schälte, Ullrich Köthe, Paul-Christian Bürkner
2023	J	`jnl`	BayesFlow: Amortized Bayesian Workflows With Neural Networks. J. Open Source Softw. Stefan T. Radev, Marvin Schmitt, Lukas Schumacher, Lasse Elsemüller, Valentin Pratz, Yannik Schälte, Ullrich Köthe, Paul-Christian Bürkner
2023	J	`jnl`	Consistency Models for Scalable and Fast Simulation-Based Inference. CoRR Marvin Schmitt, Valentin Pratz, Ullrich Köthe, Paul-Christian Bürkner, Stefan T. Radev
2023	—	`conf`	Detecting Model Misspecification in Amortized Bayesian Inference with Neural Networks. DAGM Marvin Schmitt, Paul-Christian Bürkner, Ullrich Köthe, Stefan T. Radev
2023	J	`jnl`	Finding Competence Regions in Domain Generalization. CoRR Jens Müller, Stefan T. Radev, Robert Schmier, Felix Draxler, Carsten Rother, Ullrich Köthe
2023	J	`jnl`	Finding Competence Regions in Domain Generalization. Trans. Mach. Learn. Res. Jens Müller, Stefan T. Radev, Robert Schmier, Felix Draxler, Carsten Rother, Ullrich Köthe
2023	J	`jnl`	Free-form Flows: Make Any Architecture a Normalizing Flow. CoRR Felix Draxler, Peter Sorrenson, Lea Zimmermann, Armand Rousselot, Ullrich Köthe
2023	J	`jnl`	JANA: Jointly Amortized Neural Approximation of Complex Bayesian Models. CoRR Stefan T. Radev, Marvin Schmitt, Valentin Pratz, Umberto Picchini, Ullrich Köthe, Paul-Christian Bürkner
2023	A	`conf`	Jana: Jointly amortized neural approximation of complex Bayesian models. UAI Stefan T. Radev, Marvin Schmitt, Valentin Pratz, Umberto Picchini, Ullrich Köthe, Paul-Christian Bürkner
2023	J	`jnl`	Learning Distributions on Manifolds with Free-form Flows. CoRR Peter Sorrenson, Felix Draxler, Armand Rousselot, Sander Hummerich, Ullrich Köthe
2023	J	`jnl`	Leveraging Self-Consistency for Data-Efficient Amortized Bayesian Inference. CoRR Marvin Schmitt, Daniel Habermann, Paul-Christian Bürkner, Ullrich Köthe, Stefan T. Radev
2023	J	`jnl`	Maximum Likelihood Training of Autoencoders. CoRR Peter Sorrenson, Felix Draxler, Armand Rousselot, Sander Hummerich, Lea Zimmermann, Ullrich Köthe
2023	A*	`conf`	On the Convergence Rate of Gaussianization with Random Rotations. ICML Felix Draxler, Lars Kühmichel, Armand Rousselot, Jens Müller, Christoph Schnörr, Ullrich Köthe
2023	J	`jnl`	On the Convergence Rate of Gaussianization with Random Rotations. CoRR Felix Draxler, Lars Kühmichel, Armand Rousselot, Jens Müller, Christoph Schnörr, Ullrich Köthe
2023	J	`jnl`	Positive Difference Distribution for Image Outlier Detection using Normalizing Flows and Contrastive Data. Trans. Mach. Learn. Res. Robert Schmier, Ullrich Köthe, Christoph-Nikolas Straehle
2023	J	`jnl`	Sensitivity-Aware Amortized Bayesian Inference. CoRR Lasse Elsemüller, Hans Olischläger, Marvin Schmitt, Paul-Christian Bürkner, Ullrich Köthe, Stefan T. Radev
2023	J	`jnl`	Towards Context-Aware Domain Generalization: Representing Environments with Permutation-Invariant Networks. CoRR Jens Müller, Lars Kühmichel, Martin Rohbeck, Stefan T. Radev, Ullrich Köthe
2023	J	`jnl`	Towards Learned Emulation of Interannual Water Isotopologue Variations in General Circulation Models. CoRR Jonathan Wider, Jakob Kruse, Nils Weitzel, Janica C. Bühler, Ullrich Köthe, Kira Rehfeld
2023	J	`jnl`	Training Invertible Neural Networks as Autoencoders. CoRR The-Gia Leo Nguyen, Lynton Ardizzone, Ullrich Köthe
2023	—	`conf`	Unsupervised Domain Transfer with Conditional Invertible Neural Networks. MICCAI (1) Kris K. Dreher, Leonardo Ayala, Melanie Schellenberg, Marco Hübner, Jan-Hinrich Nölke, Tim J. Adler, Silvia Seidlitz, Jan Sellner, Alexander Studier-Fischer, Janek Gröhl, Felix Nickel, Ullrich Köthe, Alexander Seitel, Lena Maier-Hein
2023	J	`jnl`	Unsupervised Domain Transfer with Conditional Invertible Neural Networks. CoRR Kris K. Dreher, Leonardo Ayala, Melanie Schellenberg, Marco Hübner, Jan-Hinrich Nölke, Tim J. Adler, Silvia Seidlitz, Jan Sellner, Alexander Studier-Fischer, Janek Gröhl, Felix Nickel, Ullrich Köthe, Alexander Seitel, Lena Maier-Hein
2022	J	`jnl`	Anomaly Detection using Contrastive Normalizing Flows. CoRR Robert Schmier, Ullrich Köthe, Christoph-Nikolas Straehle
2022	J	`jnl`	BayesFlow: Learning Complex Stochastic Models With Invertible Neural Networks. IEEE Trans. Neural Networks Learn. Syst. Stefan T. Radev, Ulf K. Mertens, Andreas Voss, Lynton Ardizzone, Ullrich Köthe
2022	—	`conf`	Content-Aware Differential Privacy with Conditional Invertible Neural Networks. DeCaF/FAIR@MICCAI Malte Tölle, Ullrich Köthe, Florian André, Benjamin Meder, Sandy Engelhardt
2022	J	`jnl`	Content-Aware Differential Privacy with Conditional Invertible Neural Networks. CoRR Malte Tölle, Ullrich Köthe, Florian André, Benjamin Meder, Sandy Engelhardt
2022	J	`jnl`	Exoplanet Characterization using Conditional Invertible Neural Networks. CoRR Jonas Haldemann, Victor Ksoll, Daniel Walter, Yann Alibert, Ralf S. Klessen, Willy Benz, Ullrich Köthe, Lynton Ardizzone, Carsten Rother
2022	A*	`conf`	Towards Multimodal Depth Estimation from Light Fields. CVPR Titus Leistner, Radek Mackowiak, Lynton Ardizzone, Ullrich Köthe, Carsten Rother
2022	J	`jnl`	Towards Multimodal Depth Estimation from Light Fields. CoRR Titus Leistner, Radek Mackowiak, Lynton Ardizzone, Ullrich Köthe, Carsten Rother
2022	A*	`conf`	Whitening Convergence Rate of Coupling-based Normalizing Flows. NeurIPS Felix Draxler, Christoph Schnörr, Ullrich Köthe
2022	J	`jnl`	Whitening Convergence Rate of Coupling-based Normalizing Flows. CoRR Felix Draxler, Christoph Schnörr, Ullrich Köthe
2021	J	`jnl`	BayesFlow can reliably detect Model Misspecification and Posterior Errors in Amortized Bayesian Inference. CoRR Marvin Schmitt, Paul-Christian Bürkner, Ullrich Köthe, Stefan T. Radev
2021	J	`jnl`	Benchmarking Invertible Architectures on Inverse Problems. CoRR Jakob Kruse, Lynton Ardizzone, Carsten Rother, Ullrich Köthe
2021	J	`jnl`	Conditional Invertible Neural Networks for Diverse Image-to-Image Translation. CoRR Lynton Ardizzone, Jakob Kruse, Carsten T. Lüth, Niels Bracher, Carsten Rother, Ullrich Köthe
2021	A*	`conf`	Generative Classifiers as a Basis for Trustworthy Image Classification. CVPR Radek Mackowiak, Lynton Ardizzone, Ullrich Köthe, Carsten Rother
2021	A*	`conf`	HINT: Hierarchical Invertible Neural Transport for Density Estimation and Bayesian Inference. AAAI Jakob Kruse, Gianluca Detommaso, Ullrich Köthe, Robert Scheichl
2021	—	`conf`	Invertible Neural Networks for Uncertainty Quantification in Photoacoustic Imaging. Bildverarbeitung für die Medizin Jan-Hinrich Nölke, Tim Adler, Janek Gröhl, Thomas Kirchner, Lynton Ardizzone, Carsten Rother, Ullrich Köthe, Lena Maier-Hein
2021	—	`conf`	Learning Robust Models Using the Principle of Independent Causal Mechanisms. GCPR Jens Müller, Robert Schmier, Lynton Ardizzone, Carsten Rother, Ullrich Köthe
2021	J	`jnl`	OutbreakFlow: Model-based Bayesian inference of disease outbreak dynamics with invertible neural networks and its application to the COVID-19 pandemics in Germany. PLoS Comput. Biol. Stefan T. Radev, Frederik Graw, Simiao Chen, Nico T. Mutters, Vanessa Eichel, Till Bärnighausen, Ullrich Köthe
2021	J	`jnl`	The Mutex Watershed and its Objective: Efficient, Parameter-Free Graph Partitioning. IEEE Trans. Pattern Anal. Mach. Intell. Steffen Wolf, Alberto Bailoni, Constantin Pape, Nasim Rahaman, Anna Kreshuk, Ullrich Köthe, Fred A. Hamprecht
2020	J	`jnl`	Amortized Bayesian model comparison with evidential deep learning. CoRR Stefan T. Radev, Marco D'Alessandro, Paul-Christian Bürkner, Ulf K. Mertens, Andreas Voss, Ullrich Köthe
2020	J	`jnl`	BayesFlow: Learning complex stochastic models with invertible neural networks. CoRR Stefan T. Radev, Ulf K. Mertens, Andreas Voss, Lynton Ardizzone, Ullrich Köthe
2020	—	`conf`	Characterizing the Role of a Single Coupling Layer in Affine Normalizing Flows. GCPR Felix Draxler, Jonathan Schwarz, Christoph Schnörr, Ullrich Köthe
2020	—	`conf`	Conditional Invertible Neural Networks for Diverse Image-to-Image Translation. GCPR Lynton Ardizzone, Jakob Kruse, Carsten T. Lüth, Niels Bracher, Carsten Rother, Ullrich Köthe
2020	A*	`conf`	Disentanglement by Nonlinear ICA with General Incompressible-flow Networks (GIN). ICLR Peter Sorrenson, Carsten Rother, Ullrich Köthe
2020	J	`jnl`	Disentanglement by Nonlinear ICA with General Incompressible-flow Networks (GIN). CoRR Peter Sorrenson, Carsten Rother, Ullrich Köthe
2020	J	`jnl`	Exact Information Bottleneck with Invertible Neural Networks: Getting the Best of Discriminative and Generative Modeling. CoRR Lynton Ardizzone, Radek Mackowiak, Ullrich Köthe, Carsten Rother
2020	J	`jnl`	Generative Classifiers as a Basis for Trustworthy Computer Vision. CoRR Radek Mackowiak, Lynton Ardizzone, Ullrich Köthe, Carsten Rother
2020	J	`jnl`	Invertible Neural Networks for Uncertainty Quantification in Photoacoustic Imaging. CoRR Jan-Hinrich Nölke, Tim Adler, Janek Gröhl, Thomas Kirchner, Lynton Ardizzone, Carsten Rother, Ullrich Köthe, Lena Maier-Hein
2020	J	`jnl`	Learning Robust Models Using The Principle of Independent Causal Mechanisms. CoRR Jens Müller, Robert Schmier, Lynton Ardizzone, Carsten Rother, Ullrich Köthe
2020	J	`jnl`	Model-based Bayesian inference of disease outbreak dynamics with invertible neural networks. CoRR Stefan T. Radev, Frederik Graw, Simiao Chen, Nico T. Mutters, Vanessa Eichel, Till Bärnighausen, Ullrich Köthe
2020	J	`jnl`	Representing Ambiguity in Registration Problems with Conditional Invertible Neural Networks. CoRR Darya Trofimova, Tim Adler, Lisa Kausch, Lynton Ardizzone, Klaus H. Maier-Hein, Ullrich Köthe, Carsten Rother, Lena Maier-Hein
2020	—	`conf`	Riemannian SOS-Polynomial Normalizing Flows. GCPR Jonathan Schwarz, Felix Draxler, Ullrich Köthe, Christoph Schnörr
2020	A*	`conf`	Training Normalizing Flows with the Information Bottleneck for Competitive Generative Classification. NeurIPS Lynton Ardizzone, Radek Mackowiak, Carsten Rother, Ullrich Köthe
2019	—	`conf`	Analyzing Inverse Problems with Invertible Neural Networks. ICLR (Poster) Lynton Ardizzone, Jakob Kruse, Carsten Rother, Ullrich Köthe
2019	J	`jnl`	Guided Image Generation with Conditional Invertible Neural Networks. CoRR Lynton Ardizzone, Carsten T. Lüth, Jakob Kruse, Carsten Rother, Ullrich Köthe
2019	J	`jnl`	HINT: Hierarchical Invertible Neural Transport for General and Sequential Bayesian inference. CoRR Gianluca Detommaso, Jakob Kruse, Lynton Ardizzone, Carsten Rother, Ullrich Köthe, Robert Scheichl
2019	—	`conf`	Object Segmentation Using Pixel-Wise Adversarial Loss. GCPR Ricard Durall, Franz-Josef Pfreundt, Ullrich Köthe, Janis Keuper
2019	J	`jnl`	Object Segmentation using Pixel-wise Adversarial Loss. CoRR Ricard Durall, Franz-Josef Pfreundt, Ullrich Köthe, Janis Keuper
2019	—	`conf`	Out of Distribution Detection for Intra-operative Functional Imaging. UNSURE/CLIP@MICCAI Tim J. Adler, Leonardo Ayala, Lynton Ardizzone, Hannes Kenngott, Anant Suraj Vemuri, Beat P. Müller-Stich, Carsten Rother, Ullrich Köthe, Lena Maier-Hein
2019	J	`jnl`	Out of distribution detection for intra-operative functional imaging. CoRR Tim J. Adler, Leonardo Ayala, Lynton Ardizzone, Hannes Kenngott, Anant Suraj Vemuri, Beat P. Müller-Stich, Carsten Rother, Ullrich Köthe, Lena Maier-Hein
2019	J	`jnl`	The Mutex Watershed and its Objective: Efficient, Parameter-Free Image Partitioning. CoRR Steffen Wolf, Alberto Bailoni, Constantin Pape, Nasim Rahaman, Anna Kreshuk, Ullrich Köthe, Fred A. Hamprecht
2019	—	`conf`	Training Invertible Neural Networks as Autoencoders. GCPR The-Gia Leo Nguyen, Lynton Ardizzone, Ullrich Köthe
2019	J	`jnl`	Uncertainty-aware performance assessment of optical imaging modalities with invertible neural networks. Int. J. Comput. Assist. Radiol. Surg. 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
2019	J	`jnl`	Uncertainty-aware performance assessment of optical imaging modalities with invertible neural networks. CoRR 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
2018	J	`jnl`	Analyzing Inverse Problems with Invertible Neural Networks. CoRR Lynton Ardizzone, Jakob Kruse, Sebastian J. Wirkert, Daniel Rahner, Eric W. Pellegrini, Ralf S. Klessen, Lena Maier-Hein, Carsten Rother, Ullrich Köthe
2018	J	`jnl`	Neuron Segmentation With High-Level Biological Priors. IEEE Trans. Medical Imaging Nikola Krasowski, Thorsten Beier, Graham Knott, Ullrich Köthe, Fred A. Hamprecht, Anna Kreshuk
2018	—	`conf`	The Mutex Watershed: Efficient, Parameter-Free Image Partitioning. ECCV (4) Steffen Wolf, Constantin Pape, Alberto Bailoni, Nasim Rahaman, Anna Kreshuk, Ullrich Köthe, Fred A. Hamprecht
2017	A*	`conf`	Learned Watershed: End-to-End Learning of Seeded Segmentation. ICCV Steffen Wolf, Lukas Schott, Ullrich Köthe, Fred A. Hamprecht
2017	J	`jnl`	Learned Watershed: End-to-End Learning of Seeded Segmentation. CoRR Steffen Wolf, Lukas Schott, Ullrich Köthe, Fred A. Hamprecht
2016	—	`conf`	An Efficient Fusion Move Algorithm for the Minimum Cost Lifted Multicut Problem. ECCV (2) Thorsten Beier, Björn Andres, Ullrich Köthe, Fred A. Hamprecht
2016	J	`jnl`	DALSA: Domain Adaptation for Supervised Learning From Sparsely Annotated MR Images. IEEE Trans. Medical Imaging Michael Götz, Christian Weber, Franciszek Binczyk, Joanna Polanska, Rafal Tarnawski, Barbara Bobek-Billewicz, Ullrich Köthe, Jens Kleesiek, Bram Stieltjes, Klaus H. Maier-Hein
2015	J	`jnl`	Graphical model for joint segmentation and tracking of multiple dividing cells. Bioinform. Martin Schiegg, Philipp Hanslovsky, Carsten Haubold, Ullrich Köthe, Lars Hufnagel, Fred A. Hamprecht
2015	—	`conf`	Improving 3D EM data segmentation by joint optimization over boundary evidence and biological priors. ISBI Nikola Krasowski, Thorsten Beier, Graham W. Knott, Ullrich Köthe, Fred A. Hamprecht, Anna Kreshuk
2015	—	`conf`	Proof-reading guidance in cell tracking by sampling from tracking-by-assignment models. ISBI Martin Schiegg, Ben Heuer, Carsten Haubold, Steffen Wolf, Ullrich Köthe, Fred A. Hamprecht
2014	—	`conf`	Asymmetric Cuts: Joint Image Labeling and Partitioning. GCPR Thorben Kröger, Jörg H. Kappes, Thorsten Beier, Ullrich Köthe, Fred A. Hamprecht
2014	A*	`conf`	Cut, Glue, & Cut: A Fast, Approximate Solver for Multicut Partitioning. CVPR Thorsten Beier, Thorben Kröger, Jörg H. Kappes, Ullrich Köthe, Fred A. Hamprecht
2014	B	`conf`	Multiple Instance Learning with Response-Optimized Random Forests. ICPR Christoph N. Straehle, Melih Kandemir, Ullrich Köthe, Fred A. Hamprecht
2014	A*	`conf`	Tracking Indistinguishable Translucent Objects over Time Using Weakly Supervised Structured Learning. CVPR Luca Fiaschi, Ferran Diego Andilla, Konstantin Gregor, Martin Schiegg, Ullrich Köthe, Marta Zlatic, Fred A. Hamprecht
2013	—	`conf`	K-Smallest Spanning Tree Segmentations. GCPR Christoph N. Straehle, Sven Peter, Ullrich Köthe, Fred A. Hamprecht
2013	—	`conf`	Learning to Segment Neurons with Non-local Quality Measures. MICCAI (2) Thorben Kröger, Shawn Mikula, Winfried Denk, Ullrich Köthe, Fred A. Hamprecht
2013	A*	`conf`	Weakly Supervised Learning of Image Partitioning Using Decision Trees with Structured Split Criteria. ICCV Christoph N. Straehle, Ullrich Köthe, Fred A. Hamprecht
2012	J	`jnl`	3D segmentation of SBFSEM images of neuropil by a graphical model over supervoxel boundaries. Medical Image Anal. Björn Andres, Ullrich Köthe, Thorben Kröger, Moritz Helmstaedter, Kevin L. Briggman, Winfried Denk, Fred A. Hamprecht
2012	—	`conf`	A Discrete Chain Graph Model for 3d+t Cell Tracking with High Misdetection Robustness. ECCV (3) Bernhard X. Kausler, Martin Schiegg, Björn Andres, Martin S. Lindner, Ullrich Köthe, Heike Leitte, Jochen Wittbrodt, Lars Hufnagel, Fred A. Hamprecht
2012	—	`ed.`	Applications of Discrete Geometry and Mathematical Morphology - First International Workshop, WADGMM 2010, Istanbul, Turkey, August 22, 2010, Revised Selected Papers WADGMM Ullrich Köthe, Annick Montanvert, Pierre Soille
2012	—	`conf`	Globally Optimal Closed-Surface Segmentation for Connectomics. ECCV (3) Björn Andres, Thorben Kröger, Kevin L. Briggman, Winfried Denk, Natalya Korogod, Graham Knott, Ullrich Köthe, Fred A. Hamprecht
2012	B	`conf`	Learning to count with regression forest and structured labels. ICPR Luca Fiaschi, Ullrich Köthe, Rahul Nair, Fred A. Hamprecht
2012	A*	`conf`	Learning to segment dense cell nuclei with shape prior. CVPR Xinghua Lou, Ullrich Köthe, Jochen Wittbrodt, Fred A. Hamprecht
2012	—	`conf`	Quality Classification of Microscopic Imagery with Weakly Supervised Learning. MLMI Xinghua Lou, Luca Fiaschi, Ullrich Köthe, Fred A. Hamprecht
2012	A*	`conf`	Seeded watershed cut uncertainty estimators for guided interactive segmentation. CVPR Christoph N. Straehle, Ullrich Köthe, Graham Knott, Kevin L. Briggman, Winfried Denk, Fred A. Hamprecht
2012	—	`conf`	The Lazy Flipper: Efficient Depth-Limited Exhaustive Search in Discrete Graphical Models. ECCV (7) Björn Andres, Jörg H. Kappes, Thorsten Beier, Ullrich Köthe, Fred A. Hamprecht
2011	—	`conf`	Automated segmentation of synapses in 3D EM data. ISBI Anna Kreshuk, Christoph N. Straehle, Christoph Sommer, Ullrich Köthe, Graham Knott, Fred A. Hamprecht
2011	—	`conf`	Carving: Scalable Interactive Segmentation of Neural Volume Electron Microscopy Images. MICCAI (1) Christoph N. Straehle, Ullrich Köthe, Graham Knott, Fred A. Hamprecht
2011	—	`conf`	Deltr: Digital embryo lineage tree reconstructor. ISBI Xinghua Lou, Frederik O. Kaster, Martin S. Lindner, Bernhard X. Kausler, Ullrich Köthe, Burkhard Hockendorf, Jochen Wittbrodt, Heike Jänicke, Fred A. Hamprecht
2011	—	`conf`	Ilastik: Interactive learning and segmentation toolkit. ISBI Christoph Sommer, Christoph N. Straehle, Ullrich Köthe, Fred A. Hamprecht
2011	—	`conf`	On Oblique Random Forests. ECML/PKDD (2) Bjoern H. Menze, B. Michael Kelm, Daniel Nicolas Splitthoff, Ullrich Köthe, Fred A. Hamprecht
2011	A*	`conf`	Probabilistic image segmentation with closedness constraints. ICCV Björn Andres, Jörg H. Kappes, Thorsten Beier, Ullrich Köthe, Fred A. Hamprecht
2011	J	`jnl`	SIMA: Simultaneous Multiple Alignment of LC/MS Peak Lists. Bioinform. Björn Voss, Michael Hanselmann, Bernhard Y. Renard, Martin S. Lindner, Ullrich Köthe, Marc Kirchner, Fred A. Hamprecht
2010	—	`conf`	An Empirical Comparison of Inference Algorithms for Graphical Models with Higher Order Factors Using OpenGM. DAGM-Symposium Björn Andres, Jörg H. Kappes, Ullrich Köthe, Christoph Schnörr, Fred A. Hamprecht
2010	J	`jnl`	Computational protein profile similarity screening for quantitative mass spectrometry experiments. Bioinform. Marc Kirchner, Bernhard Y. Renard, Ullrich Köthe, Darryl J. Pappin, Fred A. Hamprecht, Hanno Steen, Judith A. J. Steen
2010	J	`jnl`	Deuteration distribution estimation with improved sequence coverage for HX/MS experiments. Bioinform. Xinghua Lou, Marc Kirchner, Bernhard Y. Renard, Ullrich Köthe, Sebastian Boppel, Christian Graf, Chung-Tien Lee, Judith A. J. Steen, Hanno Steen, Matthias P. Mayer, Fred A. Hamprecht
2010	—	`conf`	Geometric Analysis of 3D Electron Microscopy Data. WADGMM Ullrich Köthe, Björn Andres, Thorben Kröger, Fred A. Hamprecht
2010	J	`jnl`	How to Extract the Geometry and Topology from Very Large 3D Segmentations CoRR Björn Andres, Ullrich Köthe, Thorben Kröger, Fred A. Hamprecht
2010	J	`jnl`	Runtime-Flexible Multi-dimensional Arrays and Views for C++98 and C++0x CoRR Björn Andres, Ullrich Köthe, Thorben Kröger, Fred A. Hamprecht
2010	J	`jnl`	The Lazy Flipper: MAP Inference in Higher-Order Graphical Models by Depth-limited Exhaustive Search CoRR Björn Andres, Jörg H. Kappes, Ullrich Köthe, Fred A. Hamprecht
2009	J	`jnl`	A topological sampling theorem for Robust boundary reconstruction and image segmentation. Discret. Appl. Math. Hans Meine, Ullrich Köthe, Peer Stelldinger
2009	—	`conf`	Fast and Accurate 3D Edge Detection for Surface Reconstruction. DAGM-Symposium Christian Bähnisch, Peer Stelldinger, Ullrich Köthe
2009	—	`conf`	Multivariate Watershed Segmentation of Compositional Data. DGCI Michael Hanselmann, Ullrich Köthe, Bernhard Y. Renard, Marc Kirchner, Ron M. A. Heeren, Fred A. Hamprecht
2009	—	`conf`	Pixel Approximation Errors in Common Watershed Algorithms. DGCI Hans Meine, Peer Stelldinger, Ullrich Köthe
2009	—	`conf`	Quantitative Assessment of Image Segmentation Quality by Random Walk Relaxation Times. DAGM-Symposium Björn Andres, Ullrich Köthe, Andreea Bonea, Boaz Nadler, Fred A. Hamprecht
2008	A*	`conf`	On errors-in-variables regression with arbitrary covariance and its application to optical flow estimation. CVPR Björn Andres, Claudia Kondermann, Daniel Kondermann, Ullrich Köthe, Fred A. Hamprecht, Christoph S. Garbe
2008	—	`conf`	Segmentation of SBFSEM Volume Data of Neural Tissue by Hierarchical Classification. DAGM-Symposium Björn Andres, Ullrich Köthe, Moritz Helmstaedter, Winfried Denk, Fred A. Hamprecht
2008	—	`conf`	What Can We Learn from Discrete Images about the Continuous World?. DGCI Ullrich Köthe
2006	C	`conf`	A New Sub-pixel Map for Image Analysis. IWCIA Hans Meine, Ullrich Köthe
2006	B	`conf`	Automatic cardiac MRI myocardium segmentation using graphcut. Image Processing Gunnar Kedenburg, Chris A. Cocosco, Ullrich Köthe, Wiro J. Niessen, Evert-Jan Vonken, Max A. Viergever
2006	J	`jnl`	Connectivity preserving digitization of blurred binary images in 2D and 3D. Comput. Graph. Peer Stelldinger, Ullrich Köthe
2006	—	`ch.`	Low-level Feature Detection Using the Boundary Tensor. Visualization and Processing of Tensor Fields Ullrich Köthe
2006	—	`conf`	Provably Correct Edgel Linking and Subpixel Boundary Reconstruction. DAGM-Symposium Ullrich Köthe, Peer Stelldinger, Hans Meine
2006	—	`conf`	Topologically Correct Image Segmentation Using Alpha Shapes. DGCI Peer Stelldinger, Ullrich Köthe, Hans Meine
2005	—	`conf`	GET: The Connection Between Monogenic Scale-Space and Gaussian Derivatives. Scale-Space Michael Felsberg, Ullrich Köthe
2005	—	`conf`	Riesz-Transforms Versus Derivatives: On the Relationship Between the Boundary Tensor and the Energy Tensor. Scale-Space Ullrich Köthe, Michael Felsberg
2005	—	`conf`	Shape Preserving Digitization of Binary Images After Blurring. DGCI Peer Stelldinger, Ullrich Köthe
2005	—	`conf`	The GeoMap: A Unified Representation for Topology and Geometry. GbRPR Hans Meine, Ullrich Köthe
2005	J	`jnl`	Towards a general sampling theory for shape preservation. Image Vis. Comput. Peer Stelldinger, Ullrich Köthe
2004	—	`conf`	Accurate and Efficient Approximation of the Continuous Gaussian Scale-Space. DAGM-Symposium Ullrich Köthe
2004	—	`conf`	Boundary Characterization Within the Wedge-Channel Representation. IWCM Ullrich Köthe
2004	—	`conf`	Fast and Accurate Interactive Image Segmentation in the GEOMAP Framework. Bildverarbeitung für die Medizin Hans Meine, Ullrich Köthe, H. Siegfried Stiehl
2003	—	`conf`	Edge and Junction Detection with an Improved Structure Tensor. DAGM-Symposium Ullrich Köthe
2003	A*	`conf`	Integrated Edge and Junction Detection with the Boundary Tensor. ICCV Ullrich Köthe
2003	—	`conf`	Shape Preservation during Digitization: Tight Bounds Based on the Morphing Distance. DAGM-Symposium Peer Stelldinger, Ullrich Köthe
2003	—	`conf`	Shape Preserving Digitization of Ideal and Blurred Binary Images. DGCI Ullrich Köthe, Peer Stelldinger
2002	—	`conf`	Deriving Topological Representations from Edge Images. Theoretical Foundations of Computer Vision Ullrich Köthe
2002	—	`conf`	XPMaps and Topological Segmentation - A Unified Approach to Finite Topologies in the Plane. DGCI Ullrich Köthe
2000	—	`conf`	Generic Programming Techniques that Make Planar Cell Complexes Easy to Use. Digital and Image Geometry Ullrich Köthe
1998	Misc	`conf`	Design Patterns for Independent Building Blocks. EuroPLoP Ullrich Köthe
1998	—	`conf`	The STL Model in the Geometric Domain. Generic Programming Ullrich Köthe, Karsten Weihe
1997	—	`conf`	ViComp - Architektur und Städteplanung mit virtueller Modellierung und Komposition. SimVis Andreas Schlempp, Ullrich Köthe
1996	—	`conf`	Local Appropriate Scale in Morphological Scale-Space. ECCV (1) Ullrich Köthe
1995	—	`conf`	Primary Image Segmentation. DAGM-Symposium Ullrich Köthe