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Jochen Görtler
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Books and Theses
- 2021
- [b1]Jochen Görtler:
Quantitative Methods for Uncertainty Visualization. University of Konstanz, Germany, 2021
Journal Articles
- 2022
- [j7]Rebecca Kehlbeck, Jochen Görtler, Yunhai Wang, Oliver Deussen:
SPEULER: Semantics-preserving Euler Diagrams. IEEE Trans. Vis. Comput. Graph. 28(1): 433-442 (2022) - 2021
- [j6]Kiran Gadhave, Jochen Görtler, Zach Cutler, Carolina Nobre, Oliver Deussen, Miriah Meyer, Jeff M. Phillips, Alexander Lex:
Predicting intent behind selections in scatterplot visualizations. Inf. Vis. 20(4) (2021) - 2020
- [j5]Jochen Görtler, Thilo Spinner, Dirk Streeb, Daniel Weiskopf, Oliver Deussen:
Uncertainty-Aware Principal Component Analysis. IEEE Trans. Vis. Comput. Graph. 26(1): 822-831 (2020) - 2019
- [j4]Jochen Görtler, Marc Spicker, Christoph Schulz, Daniel Weiskopf, Oliver Deussen:
Stippling of 2D Scalar Fields. IEEE Trans. Vis. Comput. Graph. 25(6): 2193-2204 (2019) - 2018
- [j3]Jochen Görtler, Christoph Schulz, Daniel Weiskopf, Oliver Deussen:
Bubble Treemaps for Uncertainty Visualization. IEEE Trans. Vis. Comput. Graph. 24(1): 719-728 (2018) - 2017
- [j2]Christoph Schulz, Arlind Nocaj, Jochen Görtler, Oliver Deussen, Ulrik Brandes, Daniel Weiskopf:
Probabilistic Graph Layout for Uncertain Network Visualization. IEEE Trans. Vis. Comput. Graph. 23(1): 531-540 (2017) - 2013
- [j1]Darko Katic, Anna-Laura Wekerle, Jochen Görtler, Patrick Spengler, Sebastian Bodenstedt, Sebastian Röhl, Stefan Suwelack, Hannes Götz Kenngott, Martin Wagner, Beat Peter Müller-Stich, Rüdiger Dillmann, Stefanie Speidel:
Context-aware Augmented Reality in laparoscopic surgery. Comput. Medical Imaging Graph. 37(2): 174-182 (2013)
Conference and Workshop Papers
- 2024
- [c4]Fred Hohman, Chaoqun Wang, Jinmook Lee, Jochen Görtler, Dominik Moritz, Jeffrey P. Bigham, Zhile Ren, Cecile Foret, Qi Shan, Xiaoyi Zhang:
Talaria: Interactively Optimizing Machine Learning Models for Efficient Inference. CHI 2024: 648:1-648:19 - 2022
- [c3]Jochen Görtler, Fred Hohman, Dominik Moritz, Kanit Wongsuphasawat, Donghao Ren, Rahul Nair, Marc Kirchner, Kayur Patel:
Neo: Generalizing Confusion Matrix Visualization to Hierarchical and Multi-Output Labels. CHI 2022: 408:1-408:13 - 2016
- [c2]Sebastian Bodenstedt, Jochen Görtler, Martin Wagner, Hannes Kenngott, Beat Peter Müller-Stich, Rüdiger Dillmann, Stefanie Speidel:
Superpixel-based structure classification for laparoscopic surgery. Medical Imaging: Image-Guided Procedures 2016: 978618 - 2015
- [c1]Sebastian Bodenstedt, Jochen Görtler, Martin Wagner, Hannes Kenngott, Beat P. Müller-Stich, Rüdiger Dillmann, Stefanie Speidel:
Strukturidentifikation mittels Superpixel in der Laparoskopie. CURAC 2015: 149-154
Data and Artifacts
- 2022
- [d1]Jochen Görtler, Thilo Spinner, Daniel Weiskopf, Oliver Deussen:
Replication Data for: Uncertainty-Aware Principal Component Analysis. DaRUS, 2022
Informal and Other Publications
- 2024
- [i4]Fred Hohman, Chaoqun Wang, Jinmook Lee, Jochen Görtler, Dominik Moritz, Jeffrey P. Bigham, Zhile Ren, Cecile Foret, Qi Shan, Xiaoyi Zhang:
Talaria: Interactively Optimizing Machine Learning Models for Efficient Inference. CoRR abs/2404.03085 (2024) - 2021
- [i3]Rebecca Kehlbeck, Jochen Görtler, Yunhai Wang, Oliver Deussen:
SpEuler: Semantics-preserving Euler Diagrams. CoRR abs/2108.03529 (2021) - [i2]Jochen Görtler, Fred Hohman, Dominik Moritz, Kanit Wongsuphasawat, Donghao Ren, Rahul Nair, Marc Kirchner, Kayur Patel:
Neo: Generalizing Confusion Matrix Visualization to Hierarchical and Multi-Output Labels. CoRR abs/2110.12536 (2021) - 2019
- [i1]Jochen Görtler, Thilo Spinner, Dirk Streeb, Daniel Weiskopf, Oliver Deussen:
Uncertainty-Aware Principal Component Analysis. CoRR abs/1905.01127 (2019)
Coauthor Index
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