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ORCIDUllrich Köthe
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- affiliation: Heidelberg University, HCI/IWR, Germany
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2020 – today
- 2024
[c81]Felix Draxler, Peter Sorrenson, Lea Zimmermann, Armand Rousselot, Ullrich Köthe:
Free-form Flows: Make Any Architecture a Normalizing Flow. AISTATS 2024: 2197-2205- [c80]Peter Sorrenson, Felix Draxler, Armand Rousselot, Sander Hummerich, Lea Zimmermann, Ullrich Köthe:
Lifting Architectural Constraints of Injective Flows. ICLR 2024 - [c79]Felix Draxler, Stefan Wahl, Christoph Schnörr, Ullrich Köthe:
On the Universality of Volume-Preserving and Coupling-Based Normalizing Flows. ICML 2024 - [c78]Marvin Schmitt, Desi R. Ivanova, Daniel Habermann, Ullrich Köthe, Paul-Christian Bürkner, Stefan T. Radev:
Leveraging Self-Consistency for Data-Efficient Amortized Bayesian Inference. ICML 2024 - [e2]Ullrich Köthe
, Carsten Rother:
Pattern Recognition - 45th DAGM German Conference, DAGM GCPR 2023, Heidelberg, Germany, September 19-22, 2023, Proceedings. Lecture Notes in Computer Science 14264, Springer 2024, ISBN 978-3-031-54604-4 [contents] - [i51]Felix Draxler, Stefan Wahl, Christoph Schnörr, Ullrich Köthe:
On the Universality of Coupling-based Normalizing Flows. CoRR abs/2402.06578 (2024) - [i50]Michael Götz, Christian Weber, Franciszek Binczyk, Joanna Polanska, Rafal Tarnawski, Barbara Bobek-Billewicz, Ullrich Köthe, Jens Kleesiek, Bram Stieltjes, Klaus H. Maier-Hein:
DALSA: Domain Adaptation for Supervised Learning From Sparsely Annotated MR Images. CoRR abs/2403.07434 (2024) - [i49]Marvin Schmitt, Paul-Christian Bürkner, Ullrich Köthe, Stefan T. Radev:
Detecting Model Misspecification in Amortized Bayesian Inference with Neural Networks: An Extended Investigation. CoRR abs/2406.03154 (2024) - [i48]Peter Lorenz, Mario Fernandez, Jens Müller, Ullrich Köthe:
Deciphering the Definition of Adversarial Robustness for post-hoc OOD Detectors. CoRR abs/2406.15104 (2024) - [i47]Peter Sorrenson, Daniel Behrend-Uriarte, Christoph Schnörr, Ullrich Köthe:
Learning Distances from Data with Normalizing Flows and Score Matching. CoRR abs/2407.09297 (2024) - [i46]Daniel Galperin, Ullrich Köthe:
Analyzing Generative Models by Manifold Entropic Metrics. CoRR abs/2410.19426 (2024) - [i45]Stefan Wahl, Armand Rousselot, Felix Draxler, Ullrich Köthe:
TRADE: Transfer of Distributions between External Conditions with Normalizing Flows. CoRR abs/2410.19492 (2024) - 2023
- [j18]Stefan T. Radev, Marvin Schmitt, Lukas Schumacher, Lasse Elsemüller, Valentin Pratz, Yannik Schälte, Ullrich Köthe, Paul-Christian Bürkner:
BayesFlow: Amortized Bayesian Workflows With Neural Networks. J. Open Source Softw. 8(90): 5702 (2023) - [j17]Jens Müller, Stefan T. Radev, Robert Schmier, Felix Draxler, Carsten Rother, Ullrich Köthe:
Finding Competence Regions in Domain Generalization. Trans. Mach. Learn. Res. 2023 (2023) - [j16]Robert Schmier, Ullrich Köthe, Christoph-Nikolas Straehle:
Positive Difference Distribution for Image Outlier Detection using Normalizing Flows and Contrastive Data. Trans. Mach. Learn. Res. 2023 (2023) - [j15]Stefan T. Radev, Marco D'Alessandro, Ulf K. Mertens, Andreas Voss, Ullrich Köthe, Paul-Christian Bürkner:
Amortized Bayesian Model Comparison With Evidential Deep Learning. IEEE Trans. Neural Networks Learn. Syst. 34(8): 4903-4917 (2023) - [c77]Marvin Schmitt, Paul-Christian Bürkner, Ullrich Köthe, Stefan T. Radev:
Detecting Model Misspecification in Amortized Bayesian Inference with Neural Networks. DAGM 2023: 541-557 - [c76]Felix Draxler, Lars Kühmichel, Armand Rousselot, Jens Müller, Christoph Schnörr, Ullrich Köthe:
On the Convergence Rate of Gaussianization with Random Rotations. ICML 2023: 8449-8468 - [c75]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:
Unsupervised Domain Transfer with Conditional Invertible Neural Networks. MICCAI (1) 2023: 770-780 - [c74]Stefan T. Radev, Marvin Schmitt, Valentin Pratz, Umberto Picchini, Ullrich Köthe, Paul-Christian Bürkner:
Jana: Jointly amortized neural approximation of complex Bayesian models. UAI 2023: 1695-1706 - [i44]Jonathan Wider, Jakob Kruse, Nils Weitzel, Janica C. Bühler, Ullrich Köthe, Kira Rehfeld:
Towards Learned Emulation of Interannual Water Isotopologue Variations in General Circulation Models. CoRR abs/2301.13462 (2023) - [i43]Stefan T. Radev, Marvin Schmitt, Valentin Pratz, Umberto Picchini, Ullrich Köthe, Paul-Christian Bürkner:
JANA: Jointly Amortized Neural Approximation of Complex Bayesian Models. CoRR abs/2302.09125 (2023) - [i42]Jens Müller, Stefan T. Radev, Robert Schmier, Felix Draxler, Carsten Rother, Ullrich Köthe:
Finding Competence Regions in Domain Generalization. CoRR abs/2303.09989 (2023) - [i41]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:
Unsupervised Domain Transfer with Conditional Invertible Neural Networks. CoRR abs/2303.10191 (2023) - [i40]The-Gia Leo Nguyen, Lynton Ardizzone, Ullrich Köthe:
Training Invertible Neural Networks as Autoencoders. CoRR abs/2303.11239 (2023) - [i39]Peter Sorrenson, Felix Draxler, Armand Rousselot, Sander Hummerich, Lea Zimmermann, Ullrich Köthe:
Maximum Likelihood Training of Autoencoders. CoRR abs/2306.01843 (2023) - [i38]Felix Draxler, Lars Kühmichel, Armand Rousselot, Jens Müller, Christoph Schnörr, Ullrich Köthe:
On the Convergence Rate of Gaussianization with Random Rotations. CoRR abs/2306.13520 (2023) - [i37]Stefan T. Radev, Marvin Schmitt, Lukas Schumacher, Lasse Elsemüller, Valentin Pratz, Yannik Schälte, Ullrich Köthe, Paul-Christian Bürkner:
BayesFlow: Amortized Bayesian Workflows With Neural Networks. CoRR abs/2306.16015 (2023) - [i36]Ullrich Köthe:
A Review of Change of Variable Formulas for Generative Modeling. CoRR abs/2308.02652 (2023) - [i35]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:
Application-driven Validation of Posteriors in Inverse Problems. CoRR abs/2309.09764 (2023) - [i34]Marvin Schmitt, Daniel Habermann, Paul-Christian Bürkner, Ullrich Köthe, Stefan T. Radev:
Leveraging Self-Consistency for Data-Efficient Amortized Bayesian Inference. CoRR abs/2310.04395 (2023) - [i33]Lasse Elsemüller, Hans Olischläger, Marvin Schmitt, Paul-Christian Bürkner, Ullrich Köthe, Stefan T. Radev:
Sensitivity-Aware Amortized Bayesian Inference. CoRR abs/2310.11122 (2023) - [i32]Felix Draxler, Peter Sorrenson, Lea Zimmermann, Armand Rousselot, Ullrich Köthe:
Free-form Flows: Make Any Architecture a Normalizing Flow. CoRR abs/2310.16624 (2023) - [i31]Marvin Schmitt, Valentin Pratz, Ullrich Köthe, Paul-Christian Bürkner, Stefan T. Radev:
Consistency Models for Scalable and Fast Simulation-Based Inference. CoRR abs/2312.05440 (2023) - [i30]Peter Sorrenson, Felix Draxler, Armand Rousselot, Sander Hummerich, Ullrich Köthe:
Learning Distributions on Manifolds with Free-form Flows. CoRR abs/2312.09852 (2023) - [i29]Jens Müller, Lars Kühmichel, Martin Rohbeck, Stefan T. Radev, Ullrich Köthe:
Towards Context-Aware Domain Generalization: Representing Environments with Permutation-Invariant Networks. CoRR abs/2312.10107 (2023) - 2022
- [j14]Stefan T. Radev, Ulf K. Mertens, Andreas Voss, Lynton Ardizzone, Ullrich Köthe:
BayesFlow: Learning Complex Stochastic Models With Invertible Neural Networks. IEEE Trans. Neural Networks Learn. Syst. 33(4): 1452-1466 (2022) - [c73]Titus Leistner, Radek Mackowiak, Lynton Ardizzone, Ullrich Köthe, Carsten Rother:
Towards Multimodal Depth Estimation from Light Fields. CVPR 2022: 12943-12951 - [c72]Malte Tölle, Ullrich Köthe, Florian André, Benjamin Meder, Sandy Engelhardt:
Content-Aware Differential Privacy with Conditional Invertible Neural Networks. DeCaF/FAIR@MICCAI 2022: 89-99 - [c71]Felix Draxler, Christoph Schnörr, Ullrich Köthe:
Whitening Convergence Rate of Coupling-based Normalizing Flows. NeurIPS 2022 - [i28]Jonas Haldemann, Victor Ksoll, Daniel Walter, Yann Alibert, Ralf S. Klessen, Willy Benz, Ullrich Köthe, Lynton Ardizzone, Carsten Rother:
Exoplanet Characterization using Conditional Invertible Neural Networks. CoRR abs/2202.00027 (2022) - [i27]Titus Leistner, Radek Mackowiak, Lynton Ardizzone, Ullrich Köthe, Carsten Rother:
Towards Multimodal Depth Estimation from Light Fields. CoRR abs/2203.16542 (2022) - [i26]Malte Tölle, Ullrich Köthe, Florian André, Benjamin Meder, Sandy Engelhardt:
Content-Aware Differential Privacy with Conditional Invertible Neural Networks. CoRR abs/2207.14625 (2022) - [i25]Robert Schmier, Ullrich Köthe, Christoph-Nikolas Straehle:
Anomaly Detection using Contrastive Normalizing Flows. CoRR abs/2208.14024 (2022) - [i24]Felix Draxler, Christoph Schnörr, Ullrich Köthe:
Whitening Convergence Rate of Coupling-based Normalizing Flows. CoRR abs/2210.14032 (2022) - 2021
- [j13]Steffen Wolf, Alberto Bailoni, Constantin Pape, Nasim Rahaman, Anna Kreshuk, Ullrich Köthe, Fred A. Hamprecht:
The Mutex Watershed and its Objective: Efficient, Parameter-Free Graph Partitioning. IEEE Trans. Pattern Anal. Mach. Intell. 43(10): 3724-3738 (2021) - [j12]Stefan T. Radev, Frederik Graw, Simiao Chen, Nico T. Mutters, Vanessa Eichel, Till Bärnighausen, Ullrich Köthe:
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. 17(10) (2021) - [c70]Jakob Kruse, Gianluca Detommaso, Ullrich Köthe, Robert Scheichl:
HINT: Hierarchical Invertible Neural Transport for Density Estimation and Bayesian Inference. AAAI 2021: 8191-8199 - [c69]Jan-Hinrich Nölke, Tim Adler, Janek Gröhl, Thomas Kirchner, Lynton Ardizzone, Carsten Rother, Ullrich Köthe, Lena Maier-Hein:
Invertible Neural Networks for Uncertainty Quantification in Photoacoustic Imaging. Bildverarbeitung für die Medizin 2021: 330-335 - [c68]Radek Mackowiak, Lynton Ardizzone, Ullrich Köthe, Carsten Rother:
Generative Classifiers as a Basis for Trustworthy Image Classification. CVPR 2021: 2971-2981 - [c67]Jens Müller, Robert Schmier, Lynton Ardizzone, Carsten Rother, Ullrich Köthe:
Learning Robust Models Using the Principle of Independent Causal Mechanisms. GCPR 2021: 79-110 - [i23]Jakob Kruse, Lynton Ardizzone, Carsten Rother, Ullrich Köthe:
Benchmarking Invertible Architectures on Inverse Problems. CoRR abs/2101.10763 (2021) - [i22]Lynton Ardizzone, Jakob Kruse, Carsten T. Lüth, Niels Bracher, Carsten Rother, Ullrich Köthe:
Conditional Invertible Neural Networks for Diverse Image-to-Image Translation. CoRR abs/2105.02104 (2021) - [i21]Marvin Schmitt, Paul-Christian Bürkner, Ullrich Köthe, Stefan T. Radev:
BayesFlow can reliably detect Model Misspecification and Posterior Errors in Amortized Bayesian Inference. CoRR abs/2112.08866 (2021) - 2020
- [c66]Felix Draxler, Jonathan Schwarz, Christoph Schnörr, Ullrich Köthe:
Characterizing the Role of a Single Coupling Layer in Affine Normalizing Flows. GCPR 2020: 1-14 - [c65]Jonathan Schwarz, Felix Draxler, Ullrich Köthe, Christoph Schnörr:
Riemannian SOS-Polynomial Normalizing Flows. GCPR 2020: 218-231 - [c64]Lynton Ardizzone, Jakob Kruse, Carsten T. Lüth, Niels Bracher, Carsten Rother, Ullrich Köthe:
Conditional Invertible Neural Networks for Diverse Image-to-Image Translation. GCPR 2020: 373-387 - [c63]Peter Sorrenson, Carsten Rother, Ullrich Köthe:
Disentanglement by Nonlinear ICA with General Incompressible-flow Networks (GIN). ICLR 2020 - [c62]Lynton Ardizzone, Radek Mackowiak, Carsten Rother, Ullrich Köthe:
Training Normalizing Flows with the Information Bottleneck for Competitive Generative Classification. NeurIPS 2020 - [i20]Peter Sorrenson, Carsten Rother, Ullrich Köthe:
Disentanglement by Nonlinear ICA with General Incompressible-flow Networks (GIN). CoRR abs/2001.04872 (2020) - [i19]Lynton Ardizzone, Radek Mackowiak, Ullrich Köthe, Carsten Rother:
Exact Information Bottleneck with Invertible Neural Networks: Getting the Best of Discriminative and Generative Modeling. CoRR abs/2001.06448 (2020) - [i18]Stefan T. Radev, Ulf K. Mertens, Andreas Voss, Lynton Ardizzone, Ullrich Köthe:
BayesFlow: Learning complex stochastic models with invertible neural networks. CoRR abs/2003.06281 (2020) - [i17]Stefan T. Radev, Marco D'Alessandro, Paul-Christian Bürkner, Ulf K. Mertens, Andreas Voss, Ullrich Köthe:
Amortized Bayesian model comparison with evidential deep learning. CoRR abs/2004.10629 (2020) - [i16]Radek Mackowiak, Lynton Ardizzone, Ullrich Köthe, Carsten Rother:
Generative Classifiers as a Basis for Trustworthy Computer Vision. CoRR abs/2007.15036 (2020) - [i15]Stefan T. Radev, Frederik Graw, Simiao Chen, Nico T. Mutters, Vanessa Eichel, Till Bärnighausen, Ullrich Köthe:
Model-based Bayesian inference of disease outbreak dynamics with invertible neural networks. CoRR abs/2010.00300 (2020) - [i14]Jens Müller, Robert Schmier, Lynton Ardizzone, Carsten Rother, Ullrich Köthe:
Learning Robust Models Using The Principle of Independent Causal Mechanisms. CoRR abs/2010.07167 (2020) - [i13]Jan-Hinrich Nölke, Tim Adler, Janek Gröhl, Thomas Kirchner, Lynton Ardizzone, Carsten Rother, Ullrich Köthe, Lena Maier-Hein:
Invertible Neural Networks for Uncertainty Quantification in Photoacoustic Imaging. CoRR abs/2011.05110 (2020) - [i12]Darya Trofimova, Tim Adler, Lisa Kausch, Lynton Ardizzone, Klaus H. Maier-Hein, Ullrich Köthe, Carsten Rother, Lena Maier-Hein:
Representing Ambiguity in Registration Problems with Conditional Invertible Neural Networks. CoRR abs/2012.08195 (2020)
2010 – 2019
- 2019
- [j11]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:
Uncertainty-aware performance assessment of optical imaging modalities with invertible neural networks. Int. J. Comput. Assist. Radiol. Surg. 14(6): 997-1007 (2019) - [c61]Ricard Durall, Franz-Josef Pfreundt, Ullrich Köthe, Janis Keuper:
Object Segmentation Using Pixel-Wise Adversarial Loss. GCPR 2019: 303-316 - [c60]The-Gia Leo Nguyen, Lynton Ardizzone, Ullrich Köthe:
Training Invertible Neural Networks as Autoencoders. GCPR 2019: 442-455 - [c59]Lynton Ardizzone, Jakob Kruse, Carsten Rother, Ullrich Köthe:
Analyzing Inverse Problems with Invertible Neural Networks. ICLR (Poster) 2019 - [c58]Tim J. Adler, Leonardo Ayala, Lynton Ardizzone, Hannes Kenngott, Anant Suraj Vemuri, Beat P. Müller-Stich, Carsten Rother, Ullrich Köthe, Lena Maier-Hein:
Out of Distribution Detection for Intra-operative Functional Imaging. UNSURE/CLIP@MICCAI 2019: 75-82 - [i11]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:
Uncertainty-aware performance assessment of optical imaging modalities with invertible neural networks. CoRR abs/1903.03441 (2019) - [i10]Steffen Wolf, Alberto Bailoni, Constantin Pape, Nasim Rahaman, Anna Kreshuk, Ullrich Köthe, Fred A. Hamprecht:
The Mutex Watershed and its Objective: Efficient, Parameter-Free Image Partitioning. CoRR abs/1904.12654 (2019) - [i9]Gianluca Detommaso, Jakob Kruse, Lynton Ardizzone, Carsten Rother, Ullrich Köthe, Robert Scheichl:
HINT: Hierarchical Invertible Neural Transport for General and Sequential Bayesian inference. CoRR abs/1905.10687 (2019) - [i8]Lynton Ardizzone, Carsten T. Lüth, Jakob Kruse, Carsten Rother, Ullrich Köthe:
Guided Image Generation with Conditional Invertible Neural Networks. CoRR abs/1907.02392 (2019) - [i7]Ricard Durall, Franz-Josef Pfreundt, Ullrich Köthe, Janis Keuper:
Object Segmentation using Pixel-wise Adversarial Loss. CoRR abs/1909.10341 (2019) - [i6]Tim J. Adler, Leonardo Ayala, Lynton Ardizzone, Hannes Kenngott, Anant Suraj Vemuri, Beat P. Müller-Stich, Carsten Rother, Ullrich Köthe, Lena Maier-Hein:
Out of distribution detection for intra-operative functional imaging. CoRR abs/1911.01877 (2019) - 2018
- [j10]Nikola Krasowski, Thorsten Beier, Graham Knott, Ullrich Köthe, Fred A. Hamprecht, Anna Kreshuk:
Neuron Segmentation With High-Level Biological Priors. IEEE Trans. Medical Imaging 37(4): 829-839 (2018) - [c57]Steffen Wolf, Constantin Pape, Alberto Bailoni, Nasim Rahaman, Anna Kreshuk, Ullrich Köthe, Fred A. Hamprecht:
The Mutex Watershed: Efficient, Parameter-Free Image Partitioning. ECCV (4) 2018: 571-587 - [i5]Lynton Ardizzone, Jakob Kruse, Sebastian J. Wirkert, Daniel Rahner, Eric W. Pellegrini, Ralf S. Klessen, Lena Maier-Hein, Carsten Rother, Ullrich Köthe:
Analyzing Inverse Problems with Invertible Neural Networks. CoRR abs/1808.04730 (2018) - 2017
- [c56]Steffen Wolf, Lukas Schott, Ullrich Köthe, Fred A. Hamprecht:
Learned Watershed: End-to-End Learning of Seeded Segmentation. ICCV 2017: 2030-2038 - [i4]Steffen Wolf, Lukas Schott, Ullrich Köthe, Fred A. Hamprecht:
Learned Watershed: End-to-End Learning of Seeded Segmentation. CoRR abs/1704.02249 (2017) - 2016
- [j9]Michael Götz, Christian Weber, Franciszek Binczyk, Joanna Polanska, Rafal Tarnawski, Barbara Bobek-Billewicz, Ullrich Köthe, Jens Kleesiek, Bram Stieltjes, Klaus H. Maier-Hein:
DALSA: Domain Adaptation for Supervised Learning From Sparsely Annotated MR Images. IEEE Trans. Medical Imaging 35(1): 184-196 (2016) - [c55]Thorsten Beier, Björn Andres, Ullrich Köthe, Fred A. Hamprecht:
An Efficient Fusion Move Algorithm for the Minimum Cost Lifted Multicut Problem. ECCV (2) 2016: 715-730 - 2015
- [j8]Martin Schiegg, Philipp Hanslovsky, Carsten Haubold, Ullrich Köthe, Lars Hufnagel, Fred A. Hamprecht:
Graphical model for joint segmentation and tracking of multiple dividing cells. Bioinform. 31(6): 948-956 (2015) - [c54]Martin Schiegg, Ben Heuer, Carsten Haubold, Steffen Wolf, Ullrich Köthe, Fred A. Hamprecht:
Proof-reading guidance in cell tracking by sampling from tracking-by-assignment models. ISBI 2015: 394-398 - [c53]Nikola Krasowski, Thorsten Beier, Graham W. Knott, Ullrich Köthe, Fred A. Hamprecht, Anna Kreshuk:
Improving 3D EM data segmentation by joint optimization over boundary evidence and biological priors. ISBI 2015: 536-539 - 2014
- [c52]Thorsten Beier, Thorben Kröger, Jörg H. Kappes, Ullrich Köthe, Fred A. Hamprecht:
Cut, Glue, & Cut: A Fast, Approximate Solver for Multicut Partitioning. CVPR 2014: 73-80 - [c51]Luca Fiaschi, Ferran Diego Andilla, Konstantin Gregor, Martin Schiegg, Ullrich Köthe, Marta Zlatic, Fred A. Hamprecht:
Tracking Indistinguishable Translucent Objects over Time Using Weakly Supervised Structured Learning. CVPR 2014: 2736-2743 - [c50]Thorben Kröger, Jörg H. Kappes, Thorsten Beier, Ullrich Köthe, Fred A. Hamprecht:
Asymmetric Cuts: Joint Image Labeling and Partitioning. GCPR 2014: 199-211 - [c49]Christoph N. Straehle, Melih Kandemir, Ullrich Köthe, Fred A. Hamprecht:
Multiple Instance Learning with Response-Optimized Random Forests. ICPR 2014: 3768-3773 - 2013
- [c48]Christoph N. Straehle, Sven Peter, Ullrich Köthe, Fred A. Hamprecht:
K-Smallest Spanning Tree Segmentations. GCPR 2013: 375-384 - [c47]Christoph N. Straehle, Ullrich Köthe, Fred A. Hamprecht:
Weakly Supervised Learning of Image Partitioning Using Decision Trees with Structured Split Criteria. ICCV 2013: 1849-1856 - [c46]Thorben Kröger, Shawn Mikula, Winfried Denk, Ullrich Köthe, Fred A. Hamprecht:
Learning to Segment Neurons with Non-local Quality Measures. MICCAI (2) 2013: 419-427 - 2012
- [j7]Björn Andres, Ullrich Köthe, Thorben Kröger, Moritz Helmstaedter, Kevin L. Briggman, Winfried Denk, Fred A. Hamprecht:
3D segmentation of SBFSEM images of neuropil by a graphical model over supervoxel boundaries. Medical Image Anal. 16(4): 796-805 (2012) - [c45]Christoph N. Straehle, Ullrich Köthe, Graham Knott, Kevin L. Briggman, Winfried Denk, Fred A. Hamprecht:
Seeded watershed cut uncertainty estimators for guided interactive segmentation. CVPR 2012: 765-772 - [c44]Xinghua Lou, Ullrich Köthe, Jochen Wittbrodt, Fred A. Hamprecht:
Learning to segment dense cell nuclei with shape prior. CVPR 2012: 1012-1018 - [c43]Bernhard X. Kausler, Martin Schiegg, Björn Andres, Martin S. Lindner, Ullrich Köthe, Heike Leitte, Jochen Wittbrodt, Lars Hufnagel, Fred A. Hamprecht:
A Discrete Chain Graph Model for 3d+t Cell Tracking with High Misdetection Robustness. ECCV (3) 2012: 144-157 - [c42]Björn Andres, Jörg H. Kappes, Thorsten Beier, Ullrich Köthe, Fred A. Hamprecht:
The Lazy Flipper: Efficient Depth-Limited Exhaustive Search in Discrete Graphical Models. ECCV (7) 2012: 154-166 - [c41]Björn Andres, Thorben Kröger, Kevin L. Briggman, Winfried Denk, Natalya Korogod, Graham Knott, Ullrich Köthe, Fred A. Hamprecht:
Globally Optimal Closed-Surface Segmentation for Connectomics. ECCV (3) 2012: 778-791 - [c40]Luca Fiaschi, Ullrich Köthe, Rahul Nair, Fred A. Hamprecht:
Learning to count with regression forest and structured labels. ICPR 2012: 2685-2688 - [c39]Xinghua Lou, Luca Fiaschi, Ullrich Köthe, Fred A. Hamprecht:
Quality Classification of Microscopic Imagery with Weakly Supervised Learning. MLMI 2012: 176-183 - [e1]Ullrich Köthe, Annick Montanvert, Pierre Soille:
Applications of Discrete Geometry and Mathematical Morphology - First International Workshop, WADGMM 2010, Istanbul, Turkey, August 22, 2010, Revised Selected Papers. Lecture Notes in Computer Science 7346, Springer 2012, ISBN 978-3-642-32312-6 [contents] - 2011
- [j6]Björn Voss, Michael Hanselmann, Bernhard Y. Renard, Martin S. Lindner, Ullrich Köthe, Marc Kirchner, Fred A. Hamprecht:
SIMA: Simultaneous Multiple Alignment of LC/MS Peak Lists. Bioinform. 27(7): 987-993 (2011) - [c38]Björn Andres, Jörg H. Kappes, Thorsten Beier, Ullrich Köthe, Fred A. Hamprecht:
Probabilistic image segmentation with closedness constraints. ICCV 2011: 2611-2618 - [c37]Anna Kreshuk, Christoph N. Straehle, Christoph Sommer, Ullrich Köthe, Graham Knott, Fred A. Hamprecht:
Automated segmentation of synapses in 3D EM data. ISBI 2011: 220-223 - [c36]Christoph Sommer, Christoph N. Straehle, Ullrich Köthe, Fred A. Hamprecht:
Ilastik: Interactive learning and segmentation toolkit. ISBI 2011: 230-233 - [c35]Xinghua Lou, Frederik O. Kaster, Martin S. Lindner, Bernhard X. Kausler, Ullrich Köthe, Burkhard Hockendorf, Jochen Wittbrodt, Heike Jänicke, Fred A. Hamprecht:
Deltr: Digital embryo lineage tree reconstructor. ISBI 2011: 1557-1560 - [c34]Christoph N. Straehle, Ullrich Köthe, Graham Knott, Fred A. Hamprecht:
Carving: Scalable Interactive Segmentation of Neural Volume Electron Microscopy Images. MICCAI (1) 2011: 653-660 - [c33]Bjoern H. Menze, B. Michael Kelm, Daniel Nicolas Splitthoff, Ullrich Köthe, Fred A. Hamprecht:
On Oblique Random Forests. ECML/PKDD (2) 2011: 453-469 - 2010
- [j5]Marc Kirchner, Bernhard Y. Renard, Ullrich Köthe, Darryl J. Pappin, Fred A. Hamprecht, Hanno Steen, Judith A. J. Steen:
Computational protein profile similarity screening for quantitative mass spectrometry experiments. Bioinform. 26(1): 77-83 (2010) - [j4]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:
Deuteration distribution estimation with improved sequence coverage for HX/MS experiments. Bioinform. 26(12): 1535-1541 (2010) - [c32]Björn Andres, Jörg H. Kappes, Ullrich Köthe, Christoph Schnörr, Fred A. Hamprecht:
An Empirical Comparison of Inference Algorithms for Graphical Models with Higher Order Factors Using OpenGM. DAGM-Symposium 2010: 353-362 - [c31]Ullrich Köthe, Björn Andres, Thorben Kröger, Fred A. Hamprecht:
Geometric Analysis of 3D Electron Microscopy Data. WADGMM 2010: 93-108 - [i3]Björn Andres, Ullrich Köthe, Thorben Kröger, Fred A. Hamprecht:
Runtime-Flexible Multi-dimensional Arrays and Views for C++98 and C++0x. CoRR abs/1008.2909 (2010) - [i2]Björn Andres, Jörg H. Kappes, Ullrich Köthe, Fred A. Hamprecht:
The Lazy Flipper: MAP Inference in Higher-Order Graphical Models by Depth-limited Exhaustive Search. CoRR abs/1009.4102 (2010) - [i1]Björn Andres, Ullrich Köthe, Thorben Kröger, Fred A. Hamprecht:
How to Extract the Geometry and Topology from Very Large 3D Segmentations. CoRR abs/1009.6215 (2010)
2000 – 2009
- 2009
- [j3]Hans Meine, Ullrich Köthe, Peer Stelldinger:
A topological sampling theorem for Robust boundary reconstruction and image segmentation. Discret. Appl. Math. 157(3): 524-541 (2009) - [c30]Christian Bähnisch, Peer Stelldinger, Ullrich Köthe:
Fast and Accurate 3D Edge Detection for Surface Reconstruction. DAGM-Symposium 2009: 111-120 - [c29]Björn Andres, Ullrich Köthe, Andreea Bonea, Boaz Nadler, Fred A. Hamprecht:
Quantitative Assessment of Image Segmentation Quality by Random Walk Relaxation Times. DAGM-Symposium 2009: 502-511 - [c28]Michael Hanselmann, Ullrich Köthe, Bernhard Y. Renard, Marc Kirchner, Ron M. A. Heeren, Fred A. Hamprecht:
Multivariate Watershed Segmentation of Compositional Data. DGCI 2009: 180-192 - [c27]Hans Meine, Peer Stelldinger, Ullrich Köthe:
Pixel Approximation Errors in Common Watershed Algorithms. DGCI 2009: 193-202 - 2008
- [c26]Björn Andres, Claudia Kondermann, Daniel Kondermann, Ullrich Köthe, Fred A. Hamprecht, Christoph S. Garbe:
On errors-in-variables regression with arbitrary covariance and its application to optical flow estimation. CVPR 2008 - [c25]Björn Andres, Ullrich Köthe, Moritz Helmstaedter, Winfried Denk, Fred A. Hamprecht:
Segmentation of SBFSEM Volume Data of Neural Tissue by Hierarchical Classification. DAGM-Symposium 2008: 142-152 - [c24]Ullrich Köthe:
What Can We Learn from Discrete Images about the Continuous World?. DGCI 2008: 4-19 - 2006
- [j2]Peer Stelldinger, Ullrich Köthe:
Connectivity preserving digitization of blurred binary images in 2D and 3D. Comput. Graph. 30(1): 70-76 (2006) - [c23]Ullrich Köthe, Peer Stelldinger, Hans Meine:
Provably Correct Edgel Linking and Subpixel Boundary Reconstruction. DAGM-Symposium 2006: 81-90 - [c22]Peer Stelldinger, Ullrich Köthe, Hans Meine:
Topologically Correct Image Segmentation Using Alpha Shapes. DGCI 2006: 542-554 - [c21]Hans Meine, Ullrich Köthe:
A New Sub-pixel Map for Image Analysis. IWCIA 2006: 116-130 - [c20]Gunnar Kedenburg, Chris A. Cocosco, Ullrich Köthe, Wiro J. Niessen, Evert-Jan Vonken, Max A. Viergever:
Automatic cardiac MRI myocardium segmentation using graphcut. Image Processing 2006: 61440A - [p1]Ullrich Köthe:
Low-level Feature Detection Using the Boundary Tensor. Visualization and Processing of Tensor Fields 2006: 63-79 - 2005
- [j1]Peer Stelldinger, Ullrich Köthe:
Towards a general sampling theory for shape preservation. Image Vis. Comput. 23(2): 237-248 (2005) - [c19]Peer Stelldinger, Ullrich Köthe:
Shape Preserving Digitization of Binary Images After Blurring. DGCI 2005: 383-391 - [c18]Hans Meine, Ullrich Köthe:
The GeoMap: A Unified Representation for Topology and Geometry. GbRPR 2005: 132-141 - [c17]Ullrich Köthe, Michael Felsberg:
Riesz-Transforms Versus Derivatives: On the Relationship Between the Boundary Tensor and the Energy Tensor. Scale-Space 2005: 179-191 - [c16]Michael Felsberg, Ullrich Köthe:
GET: The Connection Between Monogenic Scale-Space and Gaussian Derivatives. Scale-Space 2005: 192-203 - 2004
- [c15]Hans Meine, Ullrich Köthe, H. Siegfried Stiehl:
Fast and Accurate Interactive Image Segmentation in the GEOMAP Framework. Bildverarbeitung für die Medizin 2004: 60-64 - [c14]Ullrich Köthe:
Accurate and Efficient Approximation of the Continuous Gaussian Scale-Space. DAGM-Symposium 2004: 350-358 - [c13]Ullrich Köthe:
Boundary Characterization Within the Wedge-Channel Representation. IWCM 2004: 42-53 - 2003
- [c12]Ullrich Köthe:
Edge and Junction Detection with an Improved Structure Tensor. DAGM-Symposium 2003: 25-32 - [c11]Peer Stelldinger, Ullrich Köthe:
Shape Preservation during Digitization: Tight Bounds Based on the Morphing Distance. DAGM-Symposium 2003: 108-115 - [c10]Ullrich Köthe, Peer Stelldinger:
Shape Preserving Digitization of Ideal and Blurred Binary Images. DGCI 2003: 82-91 - [c9]Ullrich Köthe:
Integrated Edge and Junction Detection with the Boundary Tensor. ICCV 2003: 424-431 - 2002
- [c8]Ullrich Köthe:
XPMaps and Topological Segmentation - A Unified Approach to Finite Topologies in the Plane. DGCI 2002: 22-33 - [c7]Ullrich Köthe:
Deriving Topological Representations from Edge Images. Theoretical Foundations of Computer Vision 2002: 320-334 - 2000
- [c6]Ullrich Köthe:
Generic Programming Techniques that Make Planar Cell Complexes Easy to Use. Digital and Image Geometry 2000: 17-37
1990 – 1999
- 1998
- [c5]Ullrich Köthe, Karsten Weihe:
The STL Model in the Geometric Domain. Generic Programming 1998: 232-248 - [c4]Ullrich Köthe:
Design Patterns for Independent Building Blocks. EuroPLoP 1998: 143-166 - 1997
- [c3]Andreas Schlempp, Ullrich Köthe:
ViComp - Architektur und Städteplanung mit virtueller Modellierung und Komposition. SimVis 1997: 135-146 - 1996
- [c2]Ullrich Köthe:
Local Appropriate Scale in Morphological Scale-Space. ECCV (1) 1996: 219-228 - 1995
- [c1]Ullrich Köthe:
Primary Image Segmentation. DAGM-Symposium 1995: 554-561
Coauthor Index
Bjoern Andres
aka: Björn Andres
aka: Björn Andres
Paul C. Bürkner
aka: Paul-Christian Bürkner
aka: Paul-Christian Bürkner
Christoph N. Straehle
aka: Christoph-Nikolas Straehle
aka: Christoph-Nikolas Straehle
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