HCI Logo
Heidelberg University Logo
IWR Logo

Publications

Export 24 results:
Author Title Type [ Year(Asc)]
Filters: Author is Fred A. Hamprecht and First Letter Of Title is S  [Clear All Filters]
2019
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.PDF icon Technical Report (1.04 MB)
2018
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.
2017
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.
2016
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.PDF icon Technical Report (4.46 MB)
F. Diego and Hamprecht, F. A., “Structured Regression Gradient Boosting”, CVPR. Proceedings. pp. 1459-1467, 2016.PDF icon Technical Report (3.97 MB)
2014
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.PDF icon Technical Report (2.01 MB)
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.PDF icon Technical Report (2.6 MB)
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.PDF icon Technical Report (2.29 MB)
F. Diego and Hamprecht, F. A., “Sparse Space-Time Deconvolution for Calcium Image Analysis”, in NIPS. Proceedings, 2014, pp. 64-72.PDF icon Technical Report (5.27 MB)
X. Lou, Kloft, M., Rätsch, G., and Hamprecht, F. A., “Structured Learning from Cheap Data”, Advanced Structured Prediction. The MIT Press, 2014.PDF icon Technical Report (8.35 MB)
2012
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.PDF icon Technical Report (2.84 MB)
X. Lou and Hamprecht, F. A., “Structured Learning from Partial Annotations”, ICML 2012. Proceedings, 2012.PDF icon Technical Report (843.45 KB)
2011
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.PDF icon Technical Report (2.2 MB)
X. Lou and Hamprecht, F. A., “Structured Learning for Cell Tracking”, in NIPS 2011. Proceedings, 2011, pp. 1296-1304.PDF icon Technical Report (1.41 MB)
2009
M. Staudacher, Hamprecht, F. A., and Görlitz, L., “Self Adjustment of Scanning Electron Microscopes / Selbstadaptivität von Rasterelektronenmikroskopen”, Patent, Patent Number WO2009062781A1, 2009.PDF icon Technical Report (46.64 KB)
2008
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.PDF icon Technical Report (1.21 MB)
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.PDF icon Technical Report (1.83 MB)
2007
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.PDF icon Technical Report (229.64 KB)
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.
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.
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.PDF icon Technical Report (229.64 KB)
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.PDF icon Technical Report (872.46 KB)
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.PDF icon Technical Report (872.46 KB)
2001
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.