Theoretical investigations of NMR chemical shifts and reactivities of oxovanadium(v) compounds. - Michael Bühl; Fred A. Hamprecht (J. Comput. Chem., 1998)

A New Approach for Defect Detection in X-ray CT Images. - Heiko Eisele; Fred A. Hamprecht (DAGM-Symposium, 2002)

Chemical Library Subset Selection Algorithms: A Unified Derivation Using Spatial Statistics. - Fred A. Hamprecht; Walter Thiel; Wilfred F. van Gunsteren (J. Chem. Inf. Comput. Sci., 2002)

Two-stage Classification with Automatic Feature Selection for an Industrial Application. - Sören Hader; Fred A. Hamprecht (GfKl, 2004)

Classification of In Vivo Magnetic Resonance Spectra. - Bjoern H. Menze; Michael Wormit; Peter Bachert; Matthias Lichy; Heinz-Peter Schlemmer; Fred A. Hamprecht (GfKl, 2004)

Optimal lattices for sampling. - Hans R. Künsch; Erik Agrell; Fred A. Hamprecht (IEEE Trans. Inf. Theory, 2005)

CLARET: A Tool for Fully Automated Evaluation of MRSI with Pattern Recognition Methods. - B. Michael Kelm; Bjoern H. Menze; Thomas Neff; Christian M. Zechmann; Fred A. Hamprecht (Bildverarbeitung für die Medizin, 2006)

Machine-Based Rejection of Low-Quality Spectra and Estimation of Brain Tumor Probabilities from Magnetic Resonance Spectroscopic Images. - Bjoern H. Menze; B. Michael Kelm; Daniel Heck; Matthias Lichy; Fred A. Hamprecht (Bildverarbeitung für die Medizin, 2006)

Bayesian Estimation of Smooth Parameter Maps for Dynamic Contrast-Enhanced MR Images with Block-ICM. - B. Michael Kelm; Natalie Mueller; Bjoern H. Menze; Fred A. Hamprecht (CVPR Workshops, 2006)

From Eigenspots to Fisherspots - Latent Spaces in the Nonlinear Detection of Spot Patterns in a Highly Varying Background. - Bjoern H. Menze; B. Michael Kelm; Fred A. Hamprecht (GfKl, 2006)

Selection of Local Optical Flow Models by Means of Residual Analysis. - Björn Andres; Fred A. Hamprecht; Christoph S. Garbe (DAGM-Symposium, 2007)

Semi-supervised Tumor Detection in Magnetic Resonance Spectroscopic Images Using Discriminative Random Fields. - L. Görlitz; Bjoern H. Menze; Marc-André Weber; B. Michael Kelm; Fred A. Hamprecht (DAGM-Symposium, 2007)

On errors-in-variables regression with arbitrary covariance and its application to optical flow estimation. - Björn Andres; Claudia Kondermann; Daniel Kondermann; Ullrich Köthe; Fred A. Hamprecht; Christoph S. Garbe (CVPR, 2008)

Segmentation of SBFSEM Volume Data of Neural Tissue by Hierarchical Classification. - Björn Andres; Ullrich Köthe; Moritz Helmstaedter; Winfried Denk; Fred A. Hamprecht (DAGM-Symposium, 2008)

NITPICK: peak identification for mass spectrometry data. - Bernhard Y. Renard; Marc Kirchner; Hanno Steen; Judith A. J. Steen; Fred A. Hamprecht (BMC Bioinform., 2008)

A theoretical and experimental investigation of the systematic errors and statistical uncertainties of Time-Of-Flight-cameras. - H. Rapp; Mario Frank 001; Fred A. Hamprecht; Bernd Jähne (Int. J. Intell. Syst. Technol. Appl., 2008)

Sputter Tracking for the Automatic Monitoring of Industrial Laser-Welding Processes. - Mark Jäger; Silke Humbert; Fred A. Hamprecht (IEEE Trans. Ind. Electron., 2008)

Weakly Supervised Learning of a Classifier for Unusual Event Detection. - Mark Jäger; Christian Knoll 001; Fred A. Hamprecht (IEEE Trans. Image Process., 2008)

Quantitative Assessment of Image Segmentation Quality by Random Walk Relaxation Times. - Björn Andres; Ullrich Köthe; Andreea Bonea; Boaz Nadler; Fred A. Hamprecht (DAGM-Symposium, 2009)

Multivariate Watershed Segmentation of Compositional Data. - Michael Hanselmann; Ullrich Köthe; Bernhard Y. Renard; Marc Kirchner; Ron M. A. Heeren; Fred A. Hamprecht (DGCI, 2009)

A comparison of random forest and its Gini importance with standard chemometric methods for the feature selection and classification of spectral data. - Bjoern H. Menze; B. Michael Kelm; Ralf Masuch; Uwe Himmelreich; Peter Bachert; Wolfgang Petrich; Fred A. Hamprecht (BMC Bioinform., 2009)

Near optimum sampling design and an efficient algorithm for single tone frequency estimation. - Stefan Trittler; Fred A. Hamprecht (Digit. Signal Process., 2009)

Principal Component Imagery for the Quality Monitoring of Dynamic Laser Welding Processes. - Mark Jäger; Fred A. Hamprecht (IEEE Trans. Ind. Electron., 2009)

Estimating Kinetic Parameter Maps From Dynamic Contrast-Enhanced MRI Using Spatial Prior Knowledge. - B. Michael Kelm; Bjoern H. Menze; Oliver Nix; Christian M. Zechmann; Fred A. Hamprecht (IEEE Trans. Medical Imaging, 2009)

An Object-oriented Library for Systematic Training and Comparison of Classifiers for Computer-assisted Tumor Diagnosis from MRSI Measurements. - Frederik O. Kaster; Stephan Kassemeyer; Bernd Merkel; Oliver Nix; Fred A. Hamprecht (Bildverarbeitung für die Medizin, 2010)

An Empirical Comparison of Inference Algorithms for Graphical Models with Higher Order Factors Using OpenGM. - Björn Andres; Jörg H. Kappes; Ullrich Köthe; Christoph Schnörr; Fred A. Hamprecht (DAGM-Symposium, 2010)

Comparative Validation of Graphical Models for Learning Tumor Segmentations from Noisy Manual Annotations. - Frederik O. Kaster; Bjoern H. Menze; Marc-André Weber; Fred A. Hamprecht (MCV, 2010)

Geometric Analysis of 3D Electron Microscopy Data. - Ullrich Köthe; Björn Andres; Thorben Kröger; Fred A. Hamprecht (WADGMM, 2010)

Computational protein profile similarity screening for quantitative mass spectrometry experiments. - Marc Kirchner; Bernhard Y. Renard; Ullrich Köthe; Darryl J. Pappin; Fred A. Hamprecht; Hanno Steen; Judith A. J. Steen (Bioinform., 2010)

Deuteration distribution estimation with improved sequence coverage for HX/MS experiments. - Xinghua Lou; Marc Kirchner; Bernhard Y. Renard; Ullrich Köthe; Sebastian Boppel; Christian Graf 002; Chung-Tien Lee; Judith A. J. Steen; Hanno Steen; Matthias P. Mayer; Fred A. Hamprecht (Bioinform., 2010)

Runtime-Flexible Multi-dimensional Arrays and Views for C++98 and C++0x - Björn Andres; Ullrich Köthe; Thorben Kröger; Fred A. Hamprecht (CoRR, 2010)

The Lazy Flipper: MAP Inference in Higher-Order Graphical Models by Depth-limited Exhaustive Search - Björn Andres; Jörg H. Kappes; Ullrich Köthe; Fred A. Hamprecht (CoRR, 2010)

How to Extract the Geometry and Topology from Very Large 3D Segmentations - Björn Andres; Ullrich Köthe; Thorben Kröger; Fred A. Hamprecht (CoRR, 2010)

Probabilistic image segmentation with closedness constraints. - Björn Andres; Jörg H. Kappes; Thorsten Beier; Ullrich Köthe; Fred A. Hamprecht (ICCV, 2011)

Automated segmentation of synapses in 3D EM data. - Anna Kreshuk; Christoph N. Straehle; Christoph Sommer 002; Ullrich Köthe; Graham Knott; Fred A. Hamprecht (ISBI, 2011)

Deltr: Digital embryo lineage tree reconstructor. - Xinghua Lou; Frederik O. Kaster; Martin S. Lindner; Bernhard X. Kausler; Ullrich Köthe; Burkhard Hockendorf; Jochen Wittbrodt; Heike Jänicke; Fred A. Hamprecht (ISBI, 2011)

Ilastik: Interactive learning and segmentation toolkit. - Christoph Sommer 002; Christoph N. Straehle; Ullrich Köthe; Fred A. Hamprecht (ISBI, 2011)

Carving: Scalable Interactive Segmentation of Neural Volume Electron Microscopy Images. - Christoph N. Straehle; Ullrich Köthe; Graham Knott; Fred A. Hamprecht (MICCAI (1), 2011)

Structured Learning for Cell Tracking. - Xinghua Lou; Fred A. Hamprecht (NIPS, 2011)

On Oblique Random Forests. - Bjoern H. Menze; B. Michael Kelm; Daniel Nicolas Splitthoff; Ullrich Köthe; Fred A. Hamprecht (ECML/PKDD (2), 2011)

A Framework for Interactive Visualization and Classification of Dynamical Processes at the Water Surface. - Sven Wanner; Christoph Sommer 002; Roland Rocholz; Michael Jung; Fred A. Hamprecht; Bernd Jähne (VMV, 2011)

SIMA: Simultaneous Multiple Alignment of LC/MS Peak Lists. - Björn Voss; Michael Hanselmann; Bernhard Y. Renard; Martin S. Lindner; Ullrich Köthe; Marc Kirchner; Fred A. Hamprecht (Bioinform., 2011)

Multi-Hypothesis CRF-Segmentation of Neural Tissue in Anisotropic EM Volumes - Jan Funke; Björn Andres; Fred A. Hamprecht; Albert Cardona; Matthew Cook 001 (CoRR, 2011)

An object-oriented library for systematic training and comparison of classifiers for computer-assisted tumor diagnosis from MRSI measurements. - Frederik O. Kaster; Bernd Merkel; Oliver Nix; Fred A. Hamprecht (Comput. Sci. Res. Dev., 2011)

Efficient automatic 3D-reconstruction of branching neurons from EM data. - Jan Funke; Björn Andres; Fred A. Hamprecht; Albert Cardona; Matthew Cook 001 (CVPR, 2012)

Learning to segment dense cell nuclei with shape prior. - Xinghua Lou; Ullrich Köthe; Jochen Wittbrodt; Fred A. Hamprecht (CVPR, 2012)

Seeded watershed cut uncertainty estimators for guided interactive segmentation. - Christoph N. Straehle; Ullrich Köthe; Graham Knott; Kevin L. Briggman; Winfried Denk; Fred A. Hamprecht (CVPR, 2012)

Globally Optimal Closed-Surface Segmentation for Connectomics. - Björn Andres; Thorben Kröger; Kevin L. Briggman; Winfried Denk; Natalya Korogod; Graham Knott; Ullrich Köthe; Fred A. Hamprecht (ECCV (3), 2012)

The Lazy Flipper: Efficient Depth-Limited Exhaustive Search in Discrete Graphical Models. - Björn Andres; Jörg H. Kappes; Thorsten Beier; Ullrich Köthe; Fred A. Hamprecht (ECCV (7), 2012)

A Discrete Chain Graph Model for 3d+t Cell Tracking with High Misdetection Robustness. - Bernhard X. Kausler; Martin Schiegg; Björn Andres; Martin S. Lindner; Ullrich Köthe; Heike Leitte; Jochen Wittbrodt; Lars Hufnagel; Fred A. Hamprecht (ECCV (3), 2012)

Structured Learning from Partial Annotations. - Xinghua Lou; Fred A. Hamprecht (ICML, 2012)

Learning to count with regression forest and structured labels. - Luca Fiaschi; Ullrich Köthe; Rahul Nair; Fred A. Hamprecht (ICPR, 2012)

Learning-based mitotic cell detection in histopathological images. - Christoph Sommer 002; Luca Fiaschi; Fred A. Hamprecht; Daniel Gerlich (ICPR, 2012)

Quality Classification of Microscopic Imagery with Weakly Supervised Learning. - Xinghua Lou; Luca Fiaschi; Ullrich Köthe; Fred A. Hamprecht (MLMI, 2012)

Active Learning with Distributional Estimates. - Jens Röder; Boaz Nadler; Kevin Kunzmann; Fred A. Hamprecht (UAI, 2012)

3D segmentation of SBFSEM images of neuropil by a graphical model over supervoxel boundaries. - Björn Andres; Ullrich Köthe; Thorben Kröger; Moritz Helmstaedter; Kevin L. Briggman; Winfried Denk; Fred A. Hamprecht (Medical Image Anal., 2012)

A Comparative Study of Modern Inference Techniques for Discrete Energy Minimization Problems. - Jörg H. Kappes; Björn Andres; Fred A. Hamprecht; Christoph Schnörr; Sebastian Nowozin; Dhruv Batra; Sungwoong Kim; Bernhard X. Kausler; Jan Lellmann; Nikos Komodakis; Carsten Rother (CVPR, 2013)

K-Smallest Spanning Tree Segmentations. - Christoph N. Straehle; Sven Peter; Ullrich Köthe; Fred A. Hamprecht (GCPR, 2013)

Conservation Tracking. - Martin Schiegg; Philipp Hanslovsky; Bernhard X. Kausler; Lars Hufnagel; Fred A. Hamprecht (ICCV, 2013)

Weakly Supervised Learning of Image Partitioning Using Decision Trees with Structured Split Criteria. - Christoph N. Straehle; Ullrich Köthe; Fred A. Hamprecht (ICCV, 2013)

Automated identification of neuronal activity from calcium imaging by sparse dictionary learning. - Ferran Diego Andilla; Susanne Reichinnek; Martin Both; Fred A. Hamprecht (ISBI, 2013)

Keeping count: Leveraging temporal context to count heavily overlapping objects. - Luca Fiaschi; Gregor Konstantin; Bruno Afonso; Marta Zlatic; Fred A. Hamprecht (ISBI, 2013)

Learning to Segment Neurons with Non-local Quality Measures. - Thorben Kröger; Shawn Mikula; Winfried Denk; Ullrich Köthe; Fred A. Hamprecht (MICCAI (2), 2013)

Learning Multi-level Sparse Representations. - Ferran Diego Andilla; Fred A. Hamprecht (NIPS, 2013)

Image-based supervision of a periodically working machine. - Mario Frank 001; Fred A. Hamprecht (Pattern Anal. Appl., 2013)

Cut, Glue, & Cut: A Fast, Approximate Solver for Multicut Partitioning. - Thorsten Beier; Thorben Kröger; Jörg H. Kappes; Ullrich Köthe; Fred A. Hamprecht (CVPR, 2014)

Tracking Indistinguishable Translucent Objects over Time Using Weakly Supervised Structured Learning. - Luca Fiaschi; Ferran Diego Andilla; Konstantin Gregor; Martin Schiegg; Ullrich Köthe; Marta Zlatic; Fred A. Hamprecht (CVPR, 2014)

Semi-Global Matching: A Principled Derivation in Terms of Message Passing. - Amnon Drory; Carsten Haubold; Shai Avidan; Fred A. Hamprecht (GCPR, 2014)

Asymmetric Cuts: Joint Image Labeling and Partitioning. - Thorben Kröger; Jörg H. Kappes; Thorsten Beier; Ullrich Köthe; Fred A. Hamprecht (GCPR, 2014)

Multiple Instance Learning with Response-Optimized Random Forests. - Christoph N. Straehle; Melih Kandemir; Ullrich Köthe; Fred A. Hamprecht (ICPR, 2014)

Digital pathology: Multiple instance learning can detect Barrett's cancer. - Melih Kandemir; Annette Feuchtinger; Axel Walch; Fred A. Hamprecht (ISBI, 2014)

Automated cell nucleus detection for large-volume electron microscopy of neural tissue. - Faik Boray Tek; Thorben Kröger; Shawn Mikula; Fred A. Hamprecht (ISBI, 2014)

Yeast cell detection and segmentation in bright field microscopy. - Chong Zhang 001; Florian Huber; Michael Knop; Fred A. Hamprecht (ISBI, 2014)

Event Detection by Feature Unpredictability in Phase-Contrast Videos of Cell Cultures. - Melih Kandemir; José C. Rubio; Ute Schmidt; Christian Wojek; Johannes Welbl; Björn Ommer; Fred A. Hamprecht (MICCAI (2), 2014)

Empowering Multiple Instance Histopathology Cancer Diagnosis by Cell Graphs. - Melih Kandemir; Chong Zhang 001; Fred A. Hamprecht (MICCAI (2), 2014)

Cell Detection and Segmentation Using Correlation Clustering. - Chong Zhang 001; Julian Yarkony; Fred A. Hamprecht (MICCAI (1), 2014)

Sparse Space-Time Deconvolution for Calcium Image Analysis. - Ferran Diego Andilla; Fred A. Hamprecht (NIPS, 2014)

Parallel Multicut Segmentation via Dual Decomposition. - Julian Yarkony; Thorsten Beier; Pierre Baldi; Fred A. Hamprecht (NFMCP, 2014)

Instance Label Prediction by Dirichlet Process Multiple Instance Learning. - Melih Kandemir; Fred A. Hamprecht (UAI, 2014)

Active Structured Learning for Cell Tracking: Algorithm, Framework, and Usability. - Xinghua Lou; Martin Schiegg; Fred A. Hamprecht (IEEE Trans. Medical Imaging, 2014)

Fusion moves for correlation clustering. - Thorsten Beier; Fred A. Hamprecht; Jörg H. Kappes (CVPR, 2015)

Improving 3D EM data segmentation by joint optimization over boundary evidence and biological priors. - Nikola Krasowski; Thorsten Beier; Graham W. Knott; Ullrich Köthe; Fred A. Hamprecht; Anna Kreshuk (ISBI, 2015)

Proof-reading guidance in cell tracking by sampling from tracking-by-assignment models. - Martin Schiegg; Ben Heuer; Carsten Haubold; Steffen Wolf 001; Ullrich Köthe; Fred A. Hamprecht (ISBI, 2015)

Learning to Segment: Training Hierarchical Segmentation under a Topological Loss. - Jan Funke; Fred A. Hamprecht; Chong Zhang 001 (MICCAI (3), 2015)

Cell Event Detection in Phase-Contrast Microscopy Sequences from Few Annotations. - Melih Kandemir; Christian Wojek; Fred A. Hamprecht (MICCAI (3), 2015)

Who Is Talking to Whom: Synaptic Partner Detection in Anisotropic Volumes of Insect Brain. - Anna Kreshuk; Jan Funke; Albert Cardona; Fred A. Hamprecht (MICCAI (1), 2015)

The Deep Feed-Forward Gaussian Process: An Effective Generalization to Covariance Priors. - Melih Kandemir; Fred A. Hamprecht (FE@NIPS, 2015)

Graphical model for joint segmentation and tracking of multiple dividing cells. - Martin Schiegg; Philipp Hanslovsky; Carsten Haubold; Ullrich Köthe; Lars Hufnagel; Fred A. Hamprecht (Bioinform., 2015)

Computer-aided diagnosis from weak supervision: A benchmarking study. - Melih Kandemir; Fred A. Hamprecht (Comput. Medical Imaging Graph., 2015)

A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems. - Jörg H. Kappes; Björn Andres; Fred A. Hamprecht; Christoph Schnörr; Sebastian Nowozin; Dhruv Batra; Sungwoong Kim; Bernhard X. Kausler; Thorben Kröger; Jan Lellmann; Nikos Komodakis; Bogdan Savchynskyy; et al. (Int. J. Comput. Vis., 2015)

Variational Weakly Supervised Gaussian Processes. - Melih Kandemir; Manuel Haußmann; Ferran Diego; Kumar T. Rajamani; Jeroen van der Laak; Fred A. Hamprecht (BMVC, 2016)

Structured Regression Gradient Boosting. - Ferran Diego; Fred A. Hamprecht (CVPR, 2016)

An Efficient Fusion Move Algorithm for the Minimum Cost Lifted Multicut Problem. - Thorsten Beier; Björn Andres; Ullrich Köthe; Fred A. Hamprecht (ECCV (2), 2016)

Gaussian Process Density Counting from Weak Supervision. - Matthias von Borstel; Melih Kandemir; Philip Schmidt 001; Madhavi K. Rao; Kumar T. Rajamani; Fred A. Hamprecht (ECCV (1), 2016)

A Generalized Successive Shortest Paths Solver for Tracking Dividing Targets. - Carsten Haubold; Janez Ales; Steffen Wolf 001; Fred A. Hamprecht (ECCV (7), 2016)

Learning Diverse Models: The Coulomb Structured Support Vector Machine. - Martin Schiegg; Ferran Diego; Fred A. Hamprecht (ECCV (3), 2016)

Variational Bayesian Multiple Instance Learning with Gaussian Processes. - Manuel Haußmann; Fred A. Hamprecht; Melih Kandemir (CVPR, 2017)

Diverse M-Best Solutions by Dynamic Programming. - Carsten Haubold; Virginie Uhlmann; Michael Unser; Fred A. Hamprecht (GCPR, 2017)

Learned Watershed: End-to-End Learning of Seeded Segmentation. - Steffen Wolf 001; Lukas Schott; Ullrich Köthe; Fred A. Hamprecht (ICCV, 2017)

Cost efficient gradient boosting. - Sven Peter; Ferran Diego; Fred A. Hamprecht; Boaz Nadler (NIPS, 2017)

Sparse convolutional coding for neuronal assembly detection. - Sven Peter; Elke Kirschbaum; Martin Both; Lee Campbell; Brandon Harvey; Conor Heins; Daniel Durstewitz; Ferran Diego; Fred A. Hamprecht (NIPS, 2017)

Learning Steerable Filters for Rotation Equivariant CNNs. - Maurice Weiler; Fred A. Hamprecht; Martin Storath (CVPR, 2018)

End-to-End Learning of Deterministic Decision Trees. - Thomas M. Hehn; Fred A. Hamprecht (GCPR, 2018)

The Mutex Watershed: Efficient, Parameter-Free Image Partitioning. - Steffen Wolf 001; Constantin Pape; Alberto Bailoni; Nasim Rahaman; Anna Kreshuk; Ullrich Köthe; Fred A. Hamprecht (ECCV (4), 2018)

Essentially No Barriers in Neural Network Energy Landscape. - Felix Draxler; Kambis Veschgini; Manfred Salmhofer; Fred A. Hamprecht (ICML, 2018)

DiversePathsJ: diverse shortest paths for bioimage analysis. - Virginie Uhlmann; Carsten Haubold; Fred A. Hamprecht; Michael Unser (Bioinform., 2018)

Sampling-Free Variational Inference of Bayesian Neural Nets. - Melih Kandemir; Manuel Haußmann; Fred A. Hamprecht (CoRR, 2018)

On the Spectral Bias of Deep Neural Networks. - Nasim Rahaman; Devansh Arpit; Aristide Baratin; Felix Draxler; Min Lin; Fred A. Hamprecht; Yoshua Bengio; Aaron C. Courville (CoRR, 2018)

Neuron Segmentation With High-Level Biological Priors. - Nikola Krasowski; Thorsten Beier; Graham Knott; Ullrich Köthe; Fred A. Hamprecht; Anna Kreshuk (IEEE Trans. Medical Imaging, 2018)

End-To-End Learned Random Walker for Seeded Image Segmentation. - Lorenzo Cerrone; Alexander Zeilmann; Fred A. Hamprecht (CVPR, 2019)

LeMoNADe: Learned Motif and Neuronal Assembly Detection in calcium imaging videos. - Elke Kirschbaum; Manuel Haußmann; Steffen Wolf 001; Hannah Sonntag; Justus Schneider; Shehabeldin Elzoheiry; Oliver Kann; Daniel Durstewitz; Fred A. Hamprecht (ICLR (Poster), 2019)

On the Spectral Bias of Neural Networks. - Nasim Rahaman; Aristide Baratin; Devansh Arpit; Felix Draxler; Min Lin; Fred A. Hamprecht; Yoshua Bengio; Aaron C. Courville (ICML, 2019)

Deep Active Learning with Adaptive Acquisition. - Manuel Haußmann; Fred A. Hamprecht; Melih Kandemir (IJCAI, 2019)

Probabilistic Watershed: Sampling all spanning forests for seeded segmentation and semi-supervised learning. - Enrique Fita Sanmartin; Sebastian Damrich; Fred A. Hamprecht (NeurIPS, 2019)

Sampling-Free Variational Inference of Bayesian Neural Networks by Variance Backpropagation. - Manuel Haußmann; Fred A. Hamprecht; Melih Kandemir (UAI, 2019)

The Mutex Watershed and its Objective: Efficient, Parameter-Free Image Partitioning. - Steffen Wolf 001; Alberto Bailoni; Constantin Pape; Nasim Rahaman; Anna Kreshuk; Ullrich Köthe; Fred A. Hamprecht (CoRR, 2019)

A Generalized Framework for Agglomerative Clustering of Signed Graphs applied to Instance Segmentation. - Alberto Bailoni; Constantin Pape; Steffen Wolf 001; Thorsten Beier; Anna Kreshuk; Fred A. Hamprecht (CoRR, 2019)

DISCo for the CIA: Deep learning, Instance Segmentation, and Correlations for Calcium Imaging Analysis. - Elke Kirschbaum; Alberto Bailoni; Fred A. Hamprecht (CoRR, 2019)

Inpainting Networks Learn to Separate Cells in Microscopy Images. - Steffen Wolf 001; Fred A. Hamprecht; Jan Funke (BMVC, 2020)

Proposal-Free Volumetric Instance Segmentation from Latent Single-Instance Masks. - Alberto Bailoni; Constantin Pape; Steffen Wolf 001; Anna Kreshuk; Fred A. Hamprecht (GCPR, 2020)

The Semantic Mutex Watershed for Efficient Bottom-Up Semantic Instance Segmentation. - Steffen Wolf 001; Yuyan Li; Constantin Pape; Alberto Bailoni; Anna Kreshuk; Fred A. Hamprecht (ECCV (6), 2020)

DISCo: Deep Learning, Instance Segmentation, and Correlations for Cell Segmentation in Calcium Imaging. - Elke Kirschbaum; Alberto Bailoni; Fred A. Hamprecht (MICCAI (5), 2020)

Instance Separation Emerges from Inpainting. - Steffen Wolf 001; Fred A. Hamprecht; Jan Funke (CoRR, 2020)

End-to-End Learning of Decision Trees and Forests. - Thomas M. Hehn; Julian F. P. Kooij; Fred A. Hamprecht (Int. J. Comput. Vis., 2020)

Extensions of Karger's Algorithm: Why They Fail in Theory and How They Are Useful in Practice. - Erik Jenner; Enrique Fita Sanmartín; Fred A. Hamprecht (ICCV, 2021)

Multistar: Instance Segmentation Of Overlapping Objects With Star-Convex Polygons. - Florin C. Walter; Sebastian Damrich; Fred A. Hamprecht (ISBI, 2021)

On UMAP's True Loss Function. - Sebastian Damrich; Fred A. Hamprecht (NeurIPS, 2021)

Directed Probabilistic Watershed. - Enrique Fita Sanmartin; Sebastian Damrich; Fred A. Hamprecht (NeurIPS, 2021)

UMAP does not reproduce high-dimensional similarities due to negative sampling. - Sebastian Damrich; Fred A. Hamprecht (CoRR, 2021)

The Mutex Watershed and its Objective: Efficient, Parameter-Free Graph Partitioning. - Steffen Wolf 001; Alberto Bailoni; Constantin Pape; Nasim Rahaman; Anna Kreshuk; Ullrich Köthe; Fred A. Hamprecht (IEEE Trans. Pattern Anal. Mach. Intell., 2021)

GASP, a generalized framework for agglomerative clustering of signed graphs and its application to Instance Segmentation. - Alberto Bailoni; Constantin Pape; Nathan Hütsch; Steffen Wolf 001; Thorsten Beier; Anna Kreshuk; Fred A. Hamprecht (CVPR, 2022)

CellTypeGraph: A New Geometric Computer Vision Benchmark. - Lorenzo Cerrone; Athul Vijayan; Tejasvinee Mody; Kay Schneitz; Fred A. Hamprecht (CVPR, 2022)

The Algebraic Path Problem for Graph Metrics. - Enrique Fita Sanmartín; Sebastian Damrich; Fred A. Hamprecht (ICML, 2022)

Theory and Approximate Solvers for Branched Optimal Transport with Multiple Sources. - Peter Lippmann; Enrique Fita Sanmartín; Fred A. Hamprecht (NeurIPS, 2022)

Visualizing hierarchies in scRNA-seq data using a density tree-biased autoencoder. - Quentin Garrido; Sebastian Damrich; Alexander Jäger; Dario Cerletti; Manfred Claassen; Laurent Najman; Fred A. Hamprecht (Bioinform., 2022)

Contrastive learning unifies t-SNE and UMAP. - Sebastian Damrich; Jan Niklas Böhm; Fred A. Hamprecht; Dmitry Kobak (CoRR, 2022)

From $t$-SNE to UMAP with contrastive learning. - Sebastian Damrich; Jan Niklas Böhm; Fred A. Hamprecht; Dmitry Kobak (ICLR, 2023)

Geometric Autoencoders - What You See is What You Decode. - Philipp Nazari; Sebastian Damrich; Fred A. Hamprecht (ICML, 2023)

KineticNet: Deep learning a transferable kinetic energy functional for orbital-free density functional theory. - Roman Remme; Tobias Kaczun; Maximilian Scheurer; Andreas Dreuw; Fred A. Hamprecht (CoRR, 2023)

SynCellFactory: Generative Data Augmentation for Cell Tracking. - Moritz Sturm; Lorenzo Cerrone; Fred A. Hamprecht (MICCAI (12), 2024)

Truth is Universal: Robust Detection of Lies in LLMs. - Lennart Bürger; Fred A. Hamprecht; Boaz Nadler (NeurIPS, 2024)

The Central Spanning Tree Problem. - Enrique Fita Sanmartín; Christoph Schnörr; Fred A. Hamprecht (CoRR, 2024)

Tensor Frames - How To Make Any Message Passing Network Equivariant. - Peter Lippmann; Gerrit Gerhartz; Roman Remme; Fred A. Hamprecht (CoRR, 2024)

Expectation and Variance of the Degree of a Node in Random Spanning Trees. - Enrique Fita Sanmartín; Christoph Schnörr; Fred A. Hamprecht (CoRR, 2024)

Low-Dimensional Embeddings of High-Dimensional Data: Algorithms and Applications (Dagstuhl Seminar 24122). - Dmitry Kobak; Fred A. Hamprecht; Smita Krishnaswamy; Gal Mishne; Sebastian Damrich (Dagstuhl Reports, 2024)

Beyond Canonicalization: How Tensorial Messages Improve Equivariant Message Passing. - Peter Lippmann; Gerrit Gerhartz; Roman Remme; Fred A. Hamprecht (ICLR, 2025)

Stable and Accurate Orbital-Free DFT Powered by Machine Learning. - Roman Remme; Tobias Kaczun; Tim Ebert; Christof A. Gehrig; Dominik Geng; Gerrit Gerhartz; Marc K. Ickler; Manuel V. Klockow; Peter Lippmann; Johannes S. Schmidt; Simon Wagner; Andreas Dreuw; et al. (CoRR, 2025)

Lorentz Local Canonicalization: How to Make Any Network Lorentz-Equivariant. - Jonas Spinner; Luigi Favaro; Peter Lippmann; Sebastian Pitz; Gerrit Gerhartz; Tilman Plehn; Fred A. Hamprecht (CoRR, 2025)

Low-dimensional embeddings of high-dimensional data. - Cyril de Bodt; Alex Diaz-Papkovich; Michael Bleher; Kerstin Bunte; Corinna Coupette; Sebastian Damrich; Enrique Fita Sanmartin; Fred A. Hamprecht; Emoke-Ágnes Horvát; Dhruv Kohli; Smita Krishnaswamy; John A. Lee 001; et al. (CoRR, 2025)

Equivariance by Local Canonicalization: A Matter of Representation. - Gerrit Gerhartz; Peter Lippmann; Fred A. Hamprecht (CoRR, 2025)