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Dutzi, A (1984). Untersuchungen Zum Einfluss Der Temperatur Auf Den Gasaustausch. Institut für Umweltphysik, Fakultät für Physik und Astronomie, Univ.\ Heidelberg
Balschbach, G (2000). Untersuchungen statistischer und geometrischer Eigenschaften von Windwellen und ihrer Wechselwirkung mit der wasserseitigen Grenzschicht. Institut für Umweltphysik, Fakultät für Physik und Astronomie, Univ.\ Heidelberg. http://www.ub.uni-heidelberg.de/archiv/2473/
Popp, C (2006). Untersuchung von Austauschprozessen an der Wasseroberfläche aus Infrarot-Bildsequenzen mittels frequenzmodulierter Wärmeeinstrahlung. Institut für Umweltphysik, Fakultät für Physik und Astronomie, Univ.\ Heidelberg. http://www.ub.uni-heidelberg.de/archiv/6489
Ehrler, H (1999). Untersuchung Physiologischer Parameter Und Prozesse In Pflanzen Mit Hilfe Von Bildverarbeitung. IWR, Fakultät für Physik und Astronomie, Univ. Heidelberg
Fachat, A (1995). Untersuchung Eines 3D-Aufnahmeverfahrens Für Strömungsvorgänge An Der Wasseroberfläche. Institut für Umweltphysik, Fakultät für Physik und Astronomie, Univ. Heidelberg
Schimpf, U (2000). Untersuchung des Gasaustausches und der Mikroturbulenz an der Meeresoberfläche mittels Thermographie. Institut für Umweltphysik, Fakultät für Physik und Astronomie, Univ.\ Heidelberg. http://www.ub.uni-heidelberg.de/archiv/545
Beyer, M (1993). Untersuchung Der Relaxationszeiten Von Winderzeugten Wasseroberflächenwellen Durch Periodische Variation Der Windgeschwindigkeit. Institut für Umweltphysik, Fakultät für Physik und Astronomie, Univ.\ Heidelberg
Lauer, H (1998). Untersuchung der Neigungsstatistik von Wasseroberflächenwellen mittels eines schnellen, bildaufnehmenden Verfahrens. IWR, Fakultät für Physik und Astronomie, Univ.\ Heidelberg
Milbich, T, Bautista, M, Sutter, E and Ommer, B (2017). Unsupervised Video Understanding by Reconciliation of Posture Similarities. Proceedings of the IEEE International Conference on Computer Vision (ICCV). https://hciweb.iwr.uni-heidelberg.de/compvis/research/tmilbich_iccv17
Esser, P, Haux, J and Ommer, B (2019). Unsupervised Robust Disentangling of Latent Characteristics for Image Synthesis. Proceedings of the Intl. Conf. on Computer Vision (ICCV). https://compvis.github.io/robust-disentangling/
Milbich, T, Ghori, O and Ommer, B (2020). Unsupervised Representation Learning by Discovering Reliable Image Relations. Pattern Recognition. 102. http://arxiv.org/abs/1911.07808
Lorenz, D, Bereska, L, Milbich, T and Ommer, B (2019). Unsupervised Part-Based Disentangling of Object Shape and Appearance. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (Oral + Best paper finalist: top 45 / 5160 submissions)
Braun, S, Esser, P and Ommer, B (2020). Unsupervised Part Discovery by Unsupervised Disentanglement. Proceedings of the German Conference on Pattern Recognition (GCPR) (Oral). Tübingen. https://compvis.github.io/unsupervised-part-segmentation/
Dorkenwald, M, Büchler, U and Ommer, B (2020). Unsupervised Magnification of Posture Deviations Across Subjects. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)PDF icon article.pdf (1.15 MB)
Zisler, M, Zern, A, Petra, S and Schnörr, C (2019). Unsupervised Labeling by Geometric and Spatially Regularized Self-Assignment. Proc. SSVM. Springer
Zern, A, Zisler, M, Aström, F, Petra, S and Schnörr, C (2018). Unsupervised Label Learning on Manifolds by Spatially Regularized Geometric Assignment. GCPR. Proceedings. 698-713PDF icon Technical Report (5.23 MB)
Zern, A, Zisler, M, Aström, F, Petra, S and Schnörr, C (2018). Unsupervised Label Learning on Manifolds by Spatially Regularized Geometric Assignment. GCPR
Keuchel, J, Schnörr, C, Schellewald, C and Cremers, D (2002). Unsupervised Image Partitioning with Semidefinite Programming. Pattern Recognition, Proc. 24th DAGM Symposium. Springer, Zürich, Switzerland. 2449 141–149
Brattoli, B, Büchler, U, Dorkenwald, M, Reiser, P, Filli, L, Helmchen, F, Wahl, A - S and Ommer, B (2021). Unsupervised behaviour analysis and magnification (uBAM) using deep learning. Nature Machine Intelligence. https://rdcu.be/ch6pL
Zern, A, Zisler, M, Petra, S and Schnörr, C (2020). Unsupervised Assignment Flow: Label Learning on Feature Manifolds by Spatially Regularized Geometric Assignment. Journal of Mathematical Imaging and Vision. https://doi.org/10.1007/s10851-019-00935-7
Zern, A, Zisler, M, Petra, S and Schnörr, C (2019). Unsupervised Assignment Flow: Label Learning on Feature Manifolds by Spatially Regularized Geometric Assignment. preprint: arXiv. https://arxiv.org/abs/1904.10863
Schnörr, (1994). Unique Reconstruction of Piecewise Smooth Images by Minimizing Strictly Convex Non-Quadratic Functionals. 4 189–198
Lifermann, A, Jähne, B and Ramamonjiarisoa, A (1987). Une ètude en soufflerie de la rèflexion des hyperfrèquences par des champs de houles et de vagues. Oceanologia Acta. SP 15--22
Kirk, D S, Sellen, A J, Rother, C and Wood, K R (2006). Understanding photowork. Conference on Human Factors in Computing Systems - Proceedings. 2 761–770
Blattmann, A, Milbich, T, Dorkenwald, M and Ommer, B (2021). Understanding Object Dynamics for Interactive Image-to-Video Synthesis. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR). https://arxiv.org/abs/2106.11303v1
Bellagente, M, Haußmann, M, Luchmann, M and Plehn, T (2021). Understanding Event-Generation Networks via Uncertainties. arXiv preprint. https://arxiv.org/abs/2104.04543v1
Richmond, D, Kainmueller, D, Glocker, B, Rother, C and Myers, G (2015). Uncertainty-driven forest predictors for vertebra localization and segmentation. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 9349 653–660
Brachmann, E, Michel, F, Krull, A, Yang, M Ying, Gumhold, S and Rother, C (2016). Uncertainty-Driven 6D Pose Estimation of Objects and Scenes from a Single RGB Image. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 2016-Decem 3364–3372
Brachmann, E, Michel, F, Krull, A, Yang, M Ying, Gumhold, S and Rother, C (2016). Uncertainty-Driven 6D Pose Estimation of Objects and Scenes from a Single RGB Image. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 2016-Decem 3364–3372
Damrich, S and Hamprecht, F A (2021). On UMAP's True Loss Function. NeurIPS. Proceedings. 34PDF icon Technical Report (1.87 MB)
Damrich, S and Hamprecht, F H (2021). UMAP does not reproduce high-dimensional similarities due to negative sampling. arXiv preprint
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Peckar, W, Schnörr, C, Rohr, K and Stiehl, H S (1997). Two-Step Parameter-Free Elastic Image Registration with Prescribed Point Displacements. Proc. 9th Int. Conf. on Image Analysis and Processing (ICIAP'97). Florence, Italy
Hader, S and Hamprecht, F A (2004). Two-Stage Classification with Automatic Feature Selection for an Industrial Application. Classification, the ubiquitous challenge: Proceedings of GfKl 2004. Springer. 137-144PDF icon Technical Report (518.16 KB)
Jähne, B and Riemer, K (1990). Two-dimensional wave number spectra of small-scale water surface waves. J. Geophys. Res. 95 11531--11646
Schilling, H, Diebold, M, Rother, C and Jähne, B (2018). Trust your Model: Light Field Depth Estimation with inline Occlusion Handling. CVPR. ProceedingsPDF icon Technical Report (5.46 MB)

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