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2017
F. Aström, Hühnerbein, R., Savarino, F., Recknagel, J., and Schnörr, C., “MAP Image Labeling Using Wasserstein Messages and Geometric Assignment”, in Proc. SSVM, 2017, vol. 10302.
M. Kandemir, Hamprecht, F. A., Wojek, C., and Schmidt, U., “Maschinelles Lernen”, Patent, Patent Number WO2017032775A1, 2017.PDF icon Technical Report (317.04 KB)
B. Balluff, Hanselmann, M., and Heeren, R. M. A., “Mass spectrometry imaging for the investigation of intratumor heterogeneity”, in Advances in Cancer Research, vol. 134, Elsevier, 2017, pp. 201-230.
C. Haltebourg, “Modeling of Heat Exchange Across the Ocean Surface as Measured by Active Thermography”, vol. Dissertation. Institut für Umweltphysik, Fakultät für Physik und Astronomie, Univ. Heidelberg, 2017.
T. Beier, Pape, C., Rahaman, N., Prange, T., Berg, S., Bock, D., Cardona, A., Knott, G. W., Plaza, S. M., Scheffer, L. K., Köthe, U., Kreshuk, A., and Hamprecht, F. A., “Multicut brings automated neurite segmentation closer to human performance”, Nature Methods, vol. 14, no. 2, pp. 101-102, 2017.
2018
W. Erb, Weinmann, A., Ahlborg, M., Brandt, C., Bringout, G., Buzug, T. M., Frikel, J., Kaethner, C., Knopp, T., März, T., Möddel, M., Storath, M., and Weber, A., “Mathematical Analysis of the 1D Model and Reconstruction Schemes for Magnetic Particle Imaging”, Inverse Problems, vol. 34, no. 5, 2018.
A. Shekhovtsov, Swoboda, P., and Savchynskyy, B., “Maximum Persistency via Iterative Relaxed Inference in Graphical Models”, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 40, pp. 1668–1682, 2018.
M. Kiechle, Storath, M., Weinmann, A., and Kleinsteuber, M., “Model-based learning of local image features for unsupervised texture segmentation”, IEEE Transactions on Image Processing, vol. 27, no. 4, pp. 1994-2007, 2018.
S. Tourani, Shekhovtsov, A., Rother, C., and Savchynskyy, B., “MPLP++: Fast, Parallel Dual Block-Coordinate Ascent for Dense Graphical Models”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2018, vol. 11208 LNCS, pp. 264–281.
T. Beier, “Multicut Algorithms for Neurite Segmentation”. Heidelberg University, 2018.
S. Wolf, Pape, C., Bailoni, A., Rahaman, N., Kreshuk, A., Köthe, U., and Hamprecht, F. A., “The Mutex Watershed: Efficient, Parameter-Free Image Partitioning”, ECCV. Proceedings. Springer, pp. 571-587, 2018.
S. Wolf, Pape, C., Bailoni, A., Rahaman, N., Kreshuk, A., Köthe, U., and Hamprecht, F. A., “The Mutex Watershed: Efficient, Parameter-Free Image Partitioning”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2018, vol. 11208 LNCS, pp. 571–587.
2019
S. Peter, “Machine learning under test-time budget constraints”. Heidelberg University, 2019.
L. Nagel, Krall, K. E., and Jähne, B., “Measurement of air-sea gas transfer velocities in the Baltic Sea”, Ocean Science, vol. 15, pp. 235–247, 2019.
Y. Bengio, Deleu, T., Rahaman, N., Ke, R., Lachapelle, S., Bilaniuk, O., Goyal, A., and Pal, C., “A Meta-Transfer Objective for Learning to Disentangle Causal Mechanisms”, arXiv preprint arXiv:1901.10912, 2019.PDF icon Technical Report (871.59 KB)
B. Brattoli, Roth, K., and Ommer, B., “MIC: Mining Interclass Characteristics for Improved Metric Learning”, in Proceedings of the Intl. Conf. on Computer Vision (ICCV), 2019.
2020
S. Wolf, “Machine Learning for Instance Segmentation”. Heidelberg University, 2020.
R. Rombach, Esser, P., and Ommer, B., “Making Sense of CNNs: Interpreting Deep Representations & Their Invariances with INNs”, IEEE European Conference on Computer Vision (ECCV). 2020.
H. Schilling, Gutsche, M., Brock, A., Späth, D., Rother, C., and Krispin, K., “Mind the Gap – A Benchmark for Dense Depth Prediction beyond Lidar”, in 2nd Workshop on Safe Artificial Intelligence for Automated Driving, in conjunction with CVPR 2020, 2020.
S. Wolf, Bailoni, A., Pape, C., Rahaman, N., Kreshuk, A., Köthe, U., and Hamprecht, F. A., “The Mutex Watershed and its Objective: Efficient, Parameter-Free Graph Partitioning”, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 43, pp. 3724-3738, 2020.PDF icon Technical Report (2.58 MB)
2021
C. Pape, Remme, R., Wolny, A., Olberg, S., Wolf, S., Cerrone, L., Cortese, M., Klaus, S., Lucic, B., Ullrich, S., Anders-Össwein, M., Wolf, S., Cerikan, B., Neufeldt, C. J., Ganter, M., Schnitzler, P., Merle, U., Lusic, M., Boulant, S., Stanifer, M., Bartenschlager, R., Hamprecht, F. A., Kreshuk, A., Tischer, C., Kräusslich, H. - G., Müller, B., and Laketa, V., “Microscopy-based assay for semi-quantitative detection of SARS-CoV-2 specific antibodies in human sera”, BioEssays, vol. 43, no. 3, 2021.
F. C. Walter, Damrich, S., and Hamprecht, F. A., “MultiStar: Instance Segmentation of Overlapping Objects with Star-Convex Polygons”, ISBI. pp. 295-298, 2021.PDF icon Technical Report (1.83 MB)

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