M.  Haußmann, Hamprecht, F. A., and Kandemir, M., ?Sampling-Free Variational Inference of Bayesian Neural Networks by Variance Backpropagation?, UAI. Proceedings. pp. 563-573, 2019.

N.  Rahaman, Arpit, D., Baratin, A., Draxler, F., Lin, M., Hamprecht, F. A., Bengio, Y., and Courville, A., ?On the spectral bias of deep neural networks?, arXiv preprint arXiv:1806.08734, 2018.

S.  Peter, Kirschbaum, E., Both, M., Campbell, L. A., Harvey, B. K., Heins, C., Durstewitz, D., Diego, F., and Hamprecht, F. A., ?Sparse convolutional coding for neuronal assembly detection?, NIPS, poster. 2017.

C.  Haubold, Schiegg, M., Kreshuk, A., Berg, S., Köthe, U., and Hamprecht, F. A., ?Segmenting and Tracking Multiple Dividing Targets Using ilastik?, in Focus on Bio-Image Informatics, vol. 219, Springer, 2016, pp. 199-229.

F.  Diego and Hamprecht, F. A., ?Structured Regression Gradient Boosting?, CVPR. Proceedings. pp. 1459-1467, 2016.

B.  Maco, Cantoni, M., Holtmaat, A., Kreshuk, A., Hamprecht, F. A., and Knott, G. W., ?Semiautomated Correlative 3D Electron Microscopy of In Vivo Imaged Axons and Dendrites?, Nature Protocols, vol. 9, pp. 1354-1366, 2014.

A.  Drory, Haubold, C., Avidan, S., and Hamprecht, F. A., ?Semi-Global Matching: A Principled Derivation in Terms of Message Passing?, in GCPR. Proceedings, 2014, pp. 43-53.

U.  Köthe, Herrmannsdörfer, F., Kats, I., and Hamprecht, F. A., ?SimpleSTORM: a fast, self-calibrating reconstruction algorithm for localization microscopy?, Histochemistry and Cell Biology, vol. 141, pp. 613-627, 2014.

F.  Diego and Hamprecht, F. A., ?Sparse Space-Time Deconvolution for Calcium Image Analysis?, in NIPS. Proceedings, 2014, pp. 64-72.

X.  Lou, Kloft, M., Rätsch, G., and Hamprecht, F. A., ?Structured Learning from Cheap Data?, Advanced Structured Prediction. The MIT Press, 2014.

C. N.  Straehle, Köthe, U., Briggman, K., Denk, W., and Hamprecht, F. A., ?Seeded watershed cut uncertainty estimators for guided interactive segmentation?, in CVPR 2012. Proceedings, 2012, pp. 765 - 772.

X.  Lou and Hamprecht, F. A., ?Structured Learning from Partial Annotations?, ICML 2012. Proceedings, 2012.

M.  Hanselmann, Voss, B., Renard, B. Y., Lindner, M., Köthe, U., Kirchner, M., and Hamprecht, F. A., ?SIMA: Simultaneous Multiple Alignment of LC/MS Peak Lists?, Bioinformatics, vol. 27 (7), pp. 987-993, 2011.

X.  Lou and Hamprecht, F. A., ?Structured Learning for Cell Tracking?, in NIPS 2011. Proceedings, 2011, pp. 1296-1304.

M.  Staudacher, Hamprecht, F. A., and Görlitz, L., ?Self Adjustment of Scanning Electron Microscopes / Selbstadaptivität von Rasterelektronenmikroskopen?, Patent, Patent Number  WO2009062781A1, 2009.

B.  Andres, Köthe, U., Helmstaedter, M., Denk, W., and Hamprecht, F. A., ?Segmentation of SBFSEM Volume Data of Neural Tissue by Hierarchical Classification?, in Pattern Recognition. 30th DAGM Symposium Munich, Germany, June 10-13, 2008. Proceedings, 2008, vol. 5096, pp. 142-152.

M.  Jäger, Humbert, S., and Hamprecht, F. A., ?Sputter Tracking for the Automatic Monitoring of Industrial Laser Welding Processes?, IEEE Transactions on Industrial Electronics, vol. 55, pp. 2177-2184, 2008.

B.  Andres, Hamprecht, F. A., and Garbe, C. S., ?Selection of Local Optical Flow Models by Means of Residual Analysis?, in Pattern Recognition, 2007, vol. 4713, pp. 72-81.

B.  Andres, Garbe, C. S., Schnörr, C., and Jähne, B., ?Selection of local optical flow models by means of residual analysis?, in Proceedings of the 29th DAGM Symposium on Pattern Recognition, 2007, p. 72--81.

L.  Görlitz, Menze, B. H., Weber, M. - A., and Kelm, B. Michael, ?Semi-Supervised Tumor Detection in MRSI With Discriminative Random Fields?, in Pattern Recognition, 2007, vol. 4713, pp. 224-233.

F. A.  Hamprecht, Peter, C., Daura, X., Thiel, W., and van Gunsteren, W. F., ?A strategy for analysis of (molecular) equilibrium simulations: configuration space density estimation, clustering and visualization?, Journal of Chemical Physics, vol. 114, pp. 2079-2089, 2001.