All Publications

2019
Großkinsky, (2019). Synaptic Cleft Prediction On Electron Microsope Images. Heidelberg University Google Scholar BibTeX RTF EndNote XML
Pandey, N (2019). Weakly Supervised Semantic Segmentation. Heidelberg University Google Scholar BibTeX RTF EndNote XML
Kirschbaum, E (2019). Novel Machine Learning Approaches for Neurophysiological Data Analysis. Heidelberg University Google Scholar BibTeX RTF EndNote XML
Esposito, M, Hennersperger, C, Göbl, R, Demaret, L, Storath, M, Navab, N, Baust, M and Weinmann, A (2019). Total variation regularization of pose signals with an application to 3D freehand ultrasound. IEEE Transactions on Medical Imaging. 38(10) 2245-2258 DOI Google Scholar BibTeX RTF EndNote XML
Storath, M, Kiefer, L and Weinmann, A (2019). Smoothing for signals with discontinuities using higher order Mumford-Shah models. Numerische Mathematik. 143(2) 423-460 DOI Google Scholar BibTeX RTF EndNote XML Technical Report (1.09 MB)
Kiefer, L, Storath, M and Weinmann, A (2019). An efficient algorithm for the piecewise affine-linear Mumford-Shah model based on a Taylor jet splitting. IEEE Transactions on Image Processing. 29 DOI Google Scholar BibTeX RTF EndNote XML Technical Report (2.04 MB)
Berg, S, Kutra, D, Kroeger, T, Straehle, C N, Kausler, B X, Haubold, C, Schiegg, M, Ales, J, Beier, T, Rudy, M, Eren, K, Cervantes, J I, Xu, B, Beuttenmüller, F, Wolny, A, Zhang, C, Köthe, U, Hamprecht, F A and Kreshuk, A (2019). ilastik: interactive machine learning for (bio)image analysis. Nature Methods. 16 1226-1232 DOI Google Scholar BibTeX RTF EndNote XML
Haußmann, M, Gerwinn, S and Kandemir, M (2019). Bayesian Prior Networks with PAC Training. arXiv preprint arXiv:1906.00816 Google Scholar BibTeX RTF EndNote XML
Haußmann, M, Hamprecht, F A and Kandemir, M (2019). Deep Active Learning with Adaptive Acquisition. IJCAI. Proceedings. 2470-2476 DOI Google Scholar BibTeX RTF EndNote XML Technical Report (137.6 KB)
Haußmann, M, Hamprecht, F A and Kandemir, M (2019). Sampling-Free Variational Inference of Bayesian Neural Networks by Variance Backpropagation. UAI. Proceedings. 563-573 Google Scholar BibTeX RTF EndNote XML Technical Report (1.04 MB)
Bengio, Y, Deleu, T, Rahaman, N, Ke, R, Lachapelle, S, Bilaniuk, O, Goyal, A and Pal, C (2019). A Meta-Transfer Objective for Learning to Disentangle Causal Mechanisms. arXiv preprint arXiv:1901.10912 Google Scholar BibTeX RTF EndNote XML Technical Report (871.59 KB)
Li, Y (2019). Semantic Instance Segmentation With The Multiway Mutex Watershed. Heidelberg University Google Scholar BibTeX RTF EndNote XML
Li, J (2019). Robust Single Object Tracking Via Fully Convolutional Siamese Networks. Heidelberg University Google Scholar BibTeX RTF EndNote XML
Cerrone, L, Zeilmann, A and Hamprecht, F A (2019). End-to-End Learned Random Walker for Seeded Image Segmentation. CVPR. Proceedings. 12559-12568 DOI Google Scholar BibTeX RTF EndNote XML
Bendinger, A L, Debus, C, Glowa, C, Karger, C P, Peter, J and Storath, M (2019). Bolus arrival time estimation in dynamic contrast-enhanced magnetic resonance imaging of small animals based on spline models, in press. Physics in Medicine and Biology. 64 DOI Google Scholar BibTeX RTF EndNote XML
Kirschbaum, E, Haußmann, M, Wolf, S, Sonntag, H, Schneider, J, Elzoheiry, S, Kann, O, Durstewitz, D and Hamprecht, F A (2019). LeMoNADe: Learned Motif and Neuronal Assembly Detection in calcium imaging videos. ICLR. Proceedings Google Scholar BibTeX RTF EndNote XML

2018
Draxler, F, Veschgini, K, Salmhofer, M and Hamprecht, F A (2018). Essentially No Barriers in Neural Network Energy Landscape. ICML. Proceedings. 80 1308--1317 Google Scholar BibTeX RTF EndNote XML Technical Report (685.93 KB)
Storath, M and Weinmann, A (2018). Fast median filtering for phase or orientation data. IEEE Transactions on Pattern Analysis and Machine Intelligence. 40 639–652 DOI Google Scholar BibTeX RTF EndNote XML Technical Report (7.32 MB)
Kiechle, M, Storath, M, Weinmann, A and Kleinsteuber, M (2018). Model-based learning of local image features for unsupervised texture segmentation. IEEE Transactions on Image Processing. 27 1994-2007 Google Scholar BibTeX RTF EndNote XML
Weiler, M, Hamprecht, F A and Storath, M (2018). Learning Steerable Filters for Rotation Equivariant CNNs. CVPR. Proceedings. 849-858 DOI Google Scholar BibTeX RTF EndNote XML Technical Report (1.35 MB)
Erb, W, 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 (2018). Mathematical Analysis of the 1D Model and Reconstruction Schemes for Magnetic Particle Imaging. Inverse Problems. 34 Google Scholar BibTeX RTF EndNote XML
Schimmel, F (2018). Learnability Of Approximated Graph Cut Segmentation. Heidelberg University Google Scholar BibTeX RTF EndNote XML
Kawetzki, D (2018). Semantic Segmentation Of Urban Scenes Using Deep Learning. Heidelberg University Google Scholar BibTeX RTF EndNote XML
Bredies, K, Holler, M, Storath, M and Weinmann, A (2018). Total Generalized Variation for Manifold-valued Data. SIAM Journal on Imaging Sciences. 11 1785 - 1848 Google Scholar BibTeX RTF EndNote XML
Weilbach, C (2018). Dictionary Learning With Bayesian Gans For Few-Shot Classification. Heidelberg University Google Scholar BibTeX RTF EndNote XML
Fortun, D, Storath, M, Rickert, D, Weinmann, A and Unser, M (2018). Fast Piecewise-Affine Motion Estimation Without Segmentation. IEEE Transactions on Image Processing. 27 5612 - 5624 Google Scholar BibTeX RTF EndNote XML
Cerrone, L (2018). Deep End-To-End Learning Of A Diffusion Process For Seeded Image Segmentation. Heidelberg University Google Scholar BibTeX RTF EndNote XML
Draxler, F (2018). The Energy Landscape Of Deep Neural Networks. Heidelberg University Google Scholar BibTeX RTF EndNote XML
Wolf, S, Pape, C, Bailoni, A, Rahaman, N, Kreshuk, A, Köthe, U and Hamprecht, F A (2018). The Mutex Watershed: Efficient, Parameter-Free Image Partitioning. ECCV. Proceedings. Springer. 571-587 DOI Google Scholar BibTeX RTF EndNote XML
Hehn, T and Hamprecht, F A (2018). End-to-end Learning of Deterministic Decision Trees. German Conference on Pattern Recognition. Proceedings. Springer. LNCS 11269 612-627 DOI Google Scholar BibTeX RTF EndNote XML Technical Report (1.4 MB)
Rahaman, N, Arpit, D, Baratin, A, Draxler, F, Lin, M, Hamprecht, F A, Bengio, Y and Courville, A (2018). On the spectral bias of deep neural networks. arXiv preprint arXiv:1806.08734 Google Scholar BibTeX RTF EndNote XML
Beier, T (2018). Multicut Algorithms for Neurite Segmentation. Heidelberg University Google Scholar BibTeX RTF EndNote XML

2017
Haubold, C, Uhlmann, V, Unser, M and Hamprecht, F A (2017). Diverse M-best Solutions by Dynamic Programming. GCPR. Proceedings. Springer. LNCS 10496 255-267 DOI Google Scholar BibTeX RTF EndNote XML
Krause, G (2017). Correlation Of Performance And Entropy In Active Learning With Convolutional Neural Networks. Heidelberg University Google Scholar BibTeX RTF EndNote XML
Kandemir, M, Hamprecht, F A, Wojek, C and Schmidt, U (2017). Maschinelles Lernen. Patent, Patent Number WO2017032775A1 Google Scholar BibTeX RTF EndNote XML Technical Report (317.04 KB)
Kandemir, M, Hamprecht, F A, Wojek, C and Schmidt, U (2017). Active machine learning for training an event classification. Patent, Patent Number WO2017032775 A1 Google Scholar BibTeX RTF EndNote XML
Krasowki, N, Beier, T, Knott, G W, Köthe, U, Hamprecht, F A and Kreshuk, A (2017). Neuron Segmentation with High-Level Biological Priors. IEEE Transactions on Medical Imaging. 37 DOI Google Scholar BibTeX RTF EndNote XML
Brosowsky, M (2017). Cluster Resolving For Animal Tracking: Multi Hypotheses Tracking With Part Based Model For Object Hypotheses Generation And Pose Estimation. University of Heidelberg Google Scholar BibTeX RTF EndNote XML
Storath, M, Rickert, D, Unser, M and Weinmann, A (2017). Fast segmentation from blurred data in 3D fluorescence microscopy. IEEE Transactions on Image Processing. 26 DOI Google Scholar BibTeX RTF EndNote XML
Storath, M, Weinmann, A and Unser, M (2017). Jump-penalized least absolute values estimation of scalar or circle-valued signals. Information and Inference. 6 225–245 DOI Google Scholar BibTeX RTF EndNote XML Technical Report (3.4 MB)

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