Publications

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Heiler, M and Schnörr, C (2005). Natural Image Statistics for Natural Image Segmentation. Int. J. Comp. Vision. 63 5–19
Heiler, M and Schnörr, C (2006). Learning Sparse Representations by Non-Negative Matrix Factorization and Sequential Cone Programming. J. Mach. Learning Res. 7 1385–1407. http://www.cvgpr.uni-mannheim.de/Publications
Heiler, M and Schnörr, C (2005). Learning Sparse Image Codes by Convex Programming. Proc. Tenth IEEE Int. Conf. Computer Vision (ICCV'05). Beijing, China. 1667-1674
Heiler, M and Schnörr, C (2006). Controlling Sparseness in Non-negative Tensor Factorization. Computer Vision -- ECCV 2006. Springer. 3951 56-67PDF icon Technical Report (568.86 KB)
Heikkonen, J, Koikkalainen, P and Schnörr, C (1994). Building Trajectories via Selforganization from Spatiotemporal Features. 12th Int. Conf. on Pattern Recognition. Jerusalem, Israel
Hehn, T (2017). A Probabilistic Approach To Learn Complex Differentiable Split Functions In Decision Trees Using Gradient Ascent. Heidelberg University
Hehn, T and Hamprecht, F A (2018). End-to-end Learning of Deterministic Decision Trees. German Conference on Pattern Recognition. Proceedings. Springer. LNCS 11269 612-627PDF icon Technical Report (1.4 MB)
Hehn, T M, Kooij, J F P and Hamprecht, F A (2019). End-to-End Learning of Decision Trees and Forests. International Journal of Computer Vision. 1-15
Heers, J, Schnörr, C and Stiehl, H S (2001). Globally–Convergent Iterative Numerical Schemes for Non–Linear Variational Image Smoothing and Segmentation on a Multi–Processor Machine. IEEE Trans. Image Proc. 10 852–864
Heers, J, Schnörr, C and Stiehl, H S (1999). Investigating A Class Of Iterative Schemes And Their Parallel Implementation For Nonlinear Variational Image Smoothing And Segmentation. Comp. Sci. Dept., AB KOGS, University of Hamburg, Germany
Heers, J, Schnörr, C and Stiehl, H –S (1998). Investigation of Parallel and Globally Convergent Iterative Schemes for Nonlinear Variational Image Smoothing and Segmentation. Proc. IEEE Int. Conf. Image Proc. Chicago
Heers, J, Schnörr, C and Stiehl, H S (1998). A class of parallel algorithms for nonlinear variational image segmentation. Proc. Noblesse Workshop on Non–Linear Model Based Image Analysis (NMBIA'98). Glasgow, Scotland
Heers, J, Schnörr, C and Stiehl, H –S (1998). Parallele und global konvergente iterative Minimierung nichtlinearer Variationsansätze zur adaptiven Glättung und Segmentation von Bildern. Mustererkennung 1998. Springer, Heidelberg
Heck, D (2004). Proximity Graphs For Nonlinear Dimension Reduction. University of Heidelberg
Heck, H (2011). Bildverarbeitendes Verfahren Zur Detektion Und Vermessung Von Luftblasen An Der Wasseroberfläche Eines Blasentanks. Institut für Umweltphysik, Fakultät für Physik und Astronomie, Univ.\ Heidelberg
He, X, Wang, H, Zhang, F, Wang, G and Zhou, K (2014). Robust Simulation of Small-Scale Thin Features in SPH-based Free Surface Flows. Life.Kunzhou.Net. 1 1–8. http://doi.acm.org/10.1145/XXXXXXX.YYYYYYY http://life.kunzhou.net/2013/SPHsurfacetension.pdf
He, K, Rhemann, C, Rother, C, Tang, X and Sun, J (2011). A global sampling method for alpha matting. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 2049–2056
Hayn, M (2007). Statistical Analysis Of Spatio-Temporal Patterns In Global Nox Satellite Data. University of Heidelberg
Hayn, M, Beirle, S, Hamprecht, F A, Platt, U, Menze, B H and Wagner, T (2009). Analysing spatio-temporal patterns of the global NO2-distribution retrieved frome GOME satellite observations using a generalized additive model. Atmospheric Chemistry and Physics. 9 9367-9398PDF icon Technical Report (2.52 MB)
Haußmann, M, Gerwinn, S and Kandemir, M (2019). Bayesian Prior Networks with PAC Training. arXiv preprint arXiv:1906.00816
Haußmann, M, Hamprecht, F A and Kandemir, M (2019). Deep Active Learning with Adaptive Acquisition. IJCAI. Proceedings. 2470-2476PDF icon Technical Report (137.6 KB)
Haußmann, M, Hamprecht, F A and Kandemir, M (2017). Variational Bayesian Multiple Instance Learning with Gaussian Processes. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR). 6570-6579PDF icon Technical Report (1.29 MB)
Haußmann, (2016). Weakly Supervised Detection With Gaussian Processes. University of Heidelberg
Haußmann, M, Hamprecht, F A and Kandemir, M (2019). Sampling-Free Variational Inference of Bayesian Neural Networks by Variance Backpropagation. UAI. ProceedingsPDF icon Technical Report (1.04 MB)
Haußecker, H and Jähne, B (2000). Radiometry of imaging. Computer Vision and Applications - A Guide for Students and Practitioners. Academic Press. 85--109
Haußecker, (1996). Messung und Simulation von kleinskaligen Austauschvorgängen an der Ozeanoberfläche mittels Thermographie. IWR, Fakultät für Physik und Astronomie, Univ.\ Heidelberg
Haußecker, (1993). Mehrgitter-Bewegungssegmentierung In Bildfolgen Mit Anwendung Zur Detektion Von Sedimentverlagerungen. Institut für Umweltphysik, Fakultät für Physik und Astronomie, Univ.\ Heidelberg
Haußecker, H, Beyer, M and Jähne, B (1995). Interaction of short wind waves and turbulent shear flow as revealed by simultaneous wave slope and surface turbulence visualization. IAPSO Proceedings, XXI General Assembly, Honolulu, Hawai, August 1995, PS-10 Spatial Structure of Short Ocean Waves. 387
Haußecker, H and Fleet, D J (2001). Computing optical flow with physical models of brightness variation. IEEE Trans. Pattern Analysis Machine Intelligence. 23 661--673
Haußecker, H, Garbe, C S, Spies, H and Jähne, B (1999). A total least squares framework for low-level analysis of dynamic scenes and processes. Proceedings of the 21th DAGM Symposium on Pattern Recognition. Springer. 240--249
Haußecker, H and Jähne, B (1996). A tensor approach for local structure analysis in multi-dimensional images. 3D Image Analysis and Synthesis. 171--178
Haußecker, H, Jähne, B and Jähne, B (1995). In situ measurements of the air-sea gas transfer rate during the MBL/CoOP west coast experiment. Air-Water Gas Transfer - Selected Papers from the Third International Symposium on Air-Water Gas Transfer. AEON. 775--784
Haußecker, H and Jähne, B (1997). A tensor approach for precise computation of dense displacement vector fields. Proceedings of the 19th DAGM Symposium on Pattern Recognition, Braunschweig. Springer. 199--208
Haußecker, H and Jähne, B (1994). In-situ measurements of the air-sea gas transfer using heat as a proxy tracer. Proc. 2nd Inter. Conf. on Air-Sea Interaction and on Meteorology and Oceanography of the Coastal Zone, Lisbon, 22.--27. September 1994
Haußecker, H and Jähne, B (1993). Ein Mehrgitterverfahren zur Bewegungssegmentierung in Bildfolgen. Proc. 15. DAGM-Symposium Mustererkennung. 27--31

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