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2018
A. - S. Wahl, Erlebach, E., Brattoli, B., Büchler, U., Kaiser, J., Ineichen, V. B., Mosberger, A. C., Schneeberger, S., Imobersteg, S., Wieckhorst, M., Stirn, M., Schroeter, A., Ommer, B., and Schwab, M. E., “Early reduced behavioral activity induced by large strokes affects the efficiency of enriched environment in rats”, Sage Journals, vol. Journal of Cerebral Blood Flow & Metabolism, 2018.PDF icon 0271678x18777661.pdf (770.87 KB)
T. Hehn and Hamprecht, F. A., “End-to-end Learning of Deterministic Decision Trees”, German Conference on Pattern Recognition. Proceedings, vol. LNCS 11269. Springer, pp. 612-627, 2018.PDF icon Technical Report (1.4 MB)
F. Draxler, “The Energy Landscape of Deep Neural Networks”, Heidelberg University, 2018.
F. Draxler, Veschgini, K., Salmhofer, M., and Hamprecht, F. A., “Essentially No Barriers in Neural Network Energy Landscape”, ICML. Proceedings, vol. 80. p. 1308--1317, 2018.PDF icon Technical Report (685.93 KB)
S. Haller, Swoboda, P., and Savchynskyy, B., “Exact MAP-Inference by Confining Combinatorial Search With LP Relaxation”, in Thirty-Second AAAI Conference on Artificial Intelligence, (AAAI-18), New Orleans, Louisiana, USA, February 2-7, 2018, 2018.PDF icon 2018-02-02_aaai_dense_combilp.pdf (325.08 KB)
2019
L. Kiefer, Storath, M., and Weinmann, A., “An efficient algorithm for the piecewise affine-linear Mumford-Shah model based on a Taylor jet splitting”, IEEE Transactions on Image Processing, vol. 29, 2019.PDF icon Technical Report (2.04 MB)
L. Cerrone, Zeilmann, A., and Hamprecht, F. A., “End-to-End Learned Random Walker for Seeded Image Segmentation”, CVPR. Proceedings. pp. 12559-12568, 2019.
A. Imle, Kumberger, P., Schnellbächer, N. D., Fehr, J., Carillo-Bustamente, P., Ales, J., Schmidt, P., Ritter, C., Godinez, W. J., Müller, B., Rohr, K., Hamprecht, F. A., Schwarz, U. S., Graw, F., and Fackler, O. T., “Experimental and computational analyses reveal that environmental restrictions shape HIV-1 spread in 3D cultures”, Nature Communications, vol. 13;10(1), 2019.
E. Brachmann and Rother, C., “Expert sample consensus applied to camera re-localization”, in Proceedings of the IEEE International Conference on Computer Vision, 2019, vol. 2019-Octob, pp. 7524–7533.
D. M. Kirchhöfer, Holst, G. A., Wouters, F. S., Hock, S., and Jähne, B., “Extended noise equalisation for image compression in microscopical applications”, tm - Technisches Messen, vol. 86, pp. 422–432, 2019.
2020
T. M. Hehn, Kooij, J. F. P., and Hamprecht, F. A., “End-to-End Learning of Decision Trees and Forests”, International Journal of Computer Vision, vol. 128, pp. 997-1011, 2020.
L. Ardizzone, Mackowiak, R., Rother, C., and Köthe, U., “Exact Information Bottleneck with Invertible Neural Networks: Getting the Best of Discriminative and Generative Modeling”, 2020.PDF icon PDF (2.87 MB)
2021
M. Kandemir, Agkül, A., Haußmann, M., and Ünal, G., “Evidential Turing Processes”. arXiv preprint, 2021.
E. Jenner, Fita, E., and Hamprecht, F. A., “Extensions of Karger's Algorithm: Why They Fail in Theory and How They Are Useful in Practice”, ICCV. Proceedings. pp. 4602-4611, 2021.PDF icon Technical Report (1.1 MB)

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