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A
E. Fita, Damrich, S., and Hamprecht, F. A., “The Algebraic Path Problem for Graph Metrics”, 39th International Conference on Machine Learning, PMLR. Proceedings , vol. 162. pp. 19178-19204, 2022.
I
S. Wolf, Hamprecht, F. A., and Funke, J., “Inpainting Networks Learn to Separate Cells in Microscopy Images”, BMCV. 2020.PDF icon Technical Report (357.23 KB)
A. Andersson, Diego, F., Hamprecht, F. A., and Wählby, C., “ISTDECO: In Situ Transcriptomics Decoding by Deconvolution”, bioRxiv, 2021.
M
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.
P
A. Bailoni, Pape, C., Wolf, S., Kreshuk, A., and Hamprecht, F. A., “Proposal-Free Volumetric Instance Segmentation from Latent Single-Instance Masks”, GCPR, vol. 12544. Springer, pp. 331-344, 2020.
S
S. Wolf, Li, Y., Pape, C., Bailoni, A., Kreshuk, A., and Hamprecht, F. A., “The Semantic Mutex Watershed for Efficient Bottom-Up Semantic Instance Segmentation”, ECCV. Proceedings. pp. 208-224, 2020.
V
Q. Garrido, Damrich, S., Jäger, A., Cerletti, D., Claassen, M., Najman, L., and Hamprecht, F. A., “Visualizing hierarchies in scRNA-seq data using a density tree-biased autoencoder”, Bioinformatics, vol. 38 (Suppl 1), pp. i316-i324, 2022.